Pega Intelligent Virtual Assistant comes pre-configured to extend to Facebook Messenger, Alexa, and Google Home
Source: Techseen
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Dashbot announced today that investors have thrown their support behind its mission to be the Google Analytics for bots.
Source: VB9195
Video analytics and enterprise safety company ASADEL Technologies Pvt. Ltd has raised an undisclosed amount from Dheeraj Jain, managing partner at venture capital firm Redcliffe Capital, in exchange for a 10% stake, a company statement said.
Source: VCC11355
The topic of artificial intelligence is dominating discussions of data management this year.
Source: IM23166
40% of a typical bots' users only engage in one conversation.
Source: Topbots11850
Innovations in the areas of artificial intelligence (AI), machine learning and deep learning are beginning to dominate the technology landscape.
Source: PRNewswire9255
Just ahead of Google's I/O event kicking off later today, some details have leaked out about a new service that Google is launching for developers that are building chatbots. TechCrunch has learned that Google has developed a new service called Chatbase, which provides analytics and suggestions for how to "fix" bot experiences to make them better for users.
Source: TC14835
This chassis leasing company is deploying technology to proactively monitor its IT environment.
Source: ZDnet10788
Artificial intelligence offers feds the "tantalizing possibility" of increased speed, enhanced quality and lower costs, a Deloitte report says.
Source: FedTech16449
While debate drags on about legislation, regulations, and other measures to improve the U.S. health care system, a new wave of analytics and technology could help dramatically cut costly and unnecessary hospitalizations while improving outcomes for patients.
Source: HBR10617
ARTIFICIAL intelligence (AI) and machine learning (ML) have rapidly matured over the years and are already the norm in many fields, helping companies deploy smart systems of engagement to improve efficiency, enhance security, gain insights, and deliver superior customer experiences.
Source: Digitalnewsasia11907
Microsoft's cloud-based virtual machine for big data analytics is now available in a version running on Windows Server 2016.
Source: Eweek10842
Data science and data analytics: people working in the tech field or other related industries probably hear these terms all the time, often interchangeably.
Source: Insidebigdata23769
Understanding machine learning & data science is easy. There are numerous open courses which you can take up right now and get started. But, acquiring in-depth knowledge of a subject requires extra effort.
Source: HOB Team31380
The Indian IT industry would do well if it upgrades its capabilities and offerings in line with emerging technologies and market imperatives.
Source: Mint11952
There is more data out there than ever before, but organisations should be smart about how they use it.
Source: Gulfnews17277
How do Data Science and DevOps fit together? In this article, Richard Gall explains why integrating Data Science with your DevOps can lead to a better and smarter business.
Source: jaxenter10650
What's the one thing that makes a great data leader?
Source: Data-informed9366
Data science is the theory and practice powering the data-driven transformations we are seeing across industry and society today. Artificial intelligence (AI), self-driving cars, and predictive analytics are just a few of the breakthroughs that have been made thanks to our ever-growing ability to collect and analyze data.
Source: Data Informed17814
With SmartAI, Datameer is addressing the last mile in putting machine learning to work in business intelligence.
Source: ZDnet13041
Big Data analytics sector in India is expected to witness eight-fold growth by 2025 - from the current $2 billion to reach $16 billion, say industry experts.
Source: NDTV11385
A lot of people reach out to me. They needs jobs. But they are asking about school.
Source: Forbes10188
The chief data officer's next challenge may be to find storytellers who can explain machine learning for data science to decision-makers in the organization.
Source: Techtarget14400
Artificial intelligence-driven technology revolution is expected to impact all sectors. Some firms have already deployed AI solutions and are reaping the benefits
Source: Livemint17493
Artificial intelligence (AI) enables Siri to recognise your question, Google to correct your spelling, and tools such as Kinect to track you as you move around the room.
Source: Theconversation10443
New Invoca capability promises language pattern recognition based on the entire call vs. keyword spotting.
Source: Martechtoday10569
Artificial Intelligence is changing the way we think of technology. It is radically changing the various aspects of our daily life. Companies are now significantly making investments in AI to boost their future businesses.
Source: Knowstartup42585
Recently, I posted an interview conducted with Wes Nichols, the former CEO of MarketShare, on the ways in which data and analytics are impacting organizations (see here for the article and video). Below, I share Nichols' interesting perspective on how these changes will impact the future of marketing.
Source: Forbes9297
Machine Learning and AI are often heralded as the future of, well, every industry ever. But what about the future of Machine Learning itself? Sebastian Raschka, applied machine learning and deep learning researcher at Michigan State University and the author of Packt's best-selling book Python Machine Learning, takes a look at what's changed the most in the last few years and what's next on the horizon - here's a hint, it's not robots taking over the world.
Source: CBR12402
As organizations look for ways to better serve their customers, many are seeking new and innovative ways to better understand their customers' wants and behaviors. Increasingly, this means the use of digital tools and digital transformation initiatives, as well as the use of customer and predictive analytics, artificial intelligence (AI), and machine learning, to better know and understand their prospects' and customers' needs to provide an outstanding customer experience.
Source: Pay Before10026
A recent study from iovationon has centred on the movement towards using machine learning (ML) analytics for improving fraud mitigation and customer experience.The findings showed that while 68% of financial institutions (FIs) cite ML analytics as a high priority investment over the next few years the path to adoption will not be without its challenges. iovation and Aite Group will be hosting a webinar at 10AM PST on November 9th to discuss the results of this survey.
Source: information-age10368
The AI and advanced analytics conversation has risen all the way to C-suite. The time has come to act. Jump on the AI train soon or you will be left behind.
Source: Information Week19899
We are living in a world of data overload. From behavioral analytics to customer preferences, businesses now have so much data at their fingertips that they're unable to process and consume all of it in a meaningful way. This is where the magic of machine learning comes in.
Source: Venture Beat11952
The Delhi Police, by 2020, aspires to adopt "technology based policing" by using smart policing, artificial intelligence, and self-learning systems among other advanced technologies, it was announced on Friday.
Source: FirstPost11010
The software can learn, evolve and associate information like the human brain.
Source: Proactiveinvestors14313
The IBM Watson Data Platform already provides data scientists with the ability to crunch numbers and share large data sets across different public and private clouds. Now the company has its sights set on artificial intelligence (AI), reports Enterprise Cloud News (Banking Technology's sister publication).
Source: Banking Tech15423
Infosys is seeking to leverage artificial intelligence and data analytics to help win more business from its own Fortune 500 clients and help run their businesses better
Source: Mint10230
Does it seem like the ability to find, hire and retain data scientists is a losing battle? Is spending $500.000-plus per year for a data scientist worth it? What is a data scientist anyway?
Source: IM15237
Really you want to upgrade your skills with the best Data Analytics, Development courses, to stand out in your industry? Now Big data, Data Science, Machine Learning, Deep Learning, Artificial Intelligence (AI), Analytics, Python, R, r-stats are the most trending and highly demanding subject in every sector for almost every industry.
Source: HOB Team12807
The market for artificial intelligence (AI) technologies is flourishing. Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises.
Source: Forbes346968
Among the biggest challenges CMOs-and all marketers- face is the transformation of data into actionable insights. Consequently, it's one of the hottest topics CMOs talk about (see here).
Source: Forbes10842
Amazon Web Services (AWS) which is the cloud computing arm of Amazon, plans to get into Over-the-top (OTT) content providers market of India with their data analytics & artificial intelligence platform. Bikram Bedi, head of India region, AWS said that globally, and in India, media & entertainment has been a huge focus of the company. They work with OTT platforms or linear TV platforms like Voot, Hotstar, Netflix, Sony, Amazon Prime, Tata Sky etc.
Source: HOT Team15243
Indian AI Startups Raised About $87.85 Mn In 2017
Source: Inc4232892
Accenture hosted an AI, Data Science & Big Data Open House at The Dock to showcase the data and analytics work it does, and open up a discussion about the challenges it faces in finding data-driven solutions.
Source: Silicon Republic12441
Verizon wants to give its enterprise customers more tools to automate threat detections on networks.
Source: Zdnet10797
Actor Rajinikanth's announcement on Sunday of his plans to launch a political party may not be just a whimsical statement to buy peace with lakhs of his fans with growing aspirations. He had been doing a lot of homework and much more
Source: Times of India13611
The core of most modern Machine Learning (ML) systems is automated neural networks (ANNs). The training of ANN's require large data sets.
Source: Forbes11043
If you consider an ideal world then Mayur Datar, chief data strategist for Flipkart, wants the app of his company to understand every need of their user even before they know it. Whether it is buying a pen or a refrigerator,
Source: HOB11805
See how big data and cloud computing can be used together to manage the enormous amounts of data that are being generated on a daily basis.
Source: Dzone16182
It is largely data that has determined success, failure and change in the insurance business. However, today is different. The advent of big data technology, advanced data analytics & machine learning are changing the game entirely.
Source: HOB13146
Just consider the fact, In an average winter, Kentucky's Department of Transportation spend somewhere between $45 million to $75 million on snow removal & road salting. However, during the harsh winter of 2014-15
Source: HOB9846
There are new technologies being introduced everyday and regular advances in managing and utilizing consumer data is also happening. Resultantly, it is becoming harder to stay up to date with all of them. Technology is moving faster than marketers can figure how best to make use of it.
Source: HOB9858
AI-enhanced real estate industry could also mean agents advertising homes using virtual reality, where users can experience a home just like they experienced a new BMW on Snapchat, interacting with the property through the smartphone in their hands.
Source: Forbes13977
The trend for big businesses to set up IT hubs in India shows no sign of abating, with thousands more jobs being announced by global businesses.
Source: Computerweekly15534
The Australian Securities Exchange (ASX) has published its financial results for the first half of the year. The results showed AU$230.5 million in after-tax profit and an increase of AU$11.1 million over the year.
Source: HOB9840
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgemental error. Data Science is everywhere and here is the rescue for how to be a data scientist.
Source: HOB23511
Cloudera, Inc., (NYSE: CLDR), the modern platform for machine learning and analytics, optimized for the cloud, announced Cloudera Altus with SDX, the first machine learning and analytics Platform-as-a-Service (PaaS), built with a shared data catalog providing the business context of that data.
Source: PR Newswire11862
It's as good a time as any to keep yourself updated - especially for those who are in the ever-changing technology field. If you're interested in, or working as a professional in Data Science, Machine Learning and allied fields, we've compiled a list of top 11 books that are available free that you must catch up on gloomy rainy days.
Source: HOB26862
Strong math understanding, computing skills, critical thinking and presentations skills provide a strong foundation for a career in Data Science.
Source: Kdnugget9636
If we look back, there is a huge progress in the field of technology and innovations. Many technologies emerge as the future starts and today, some of them are on their way up in the industry. Technologies like Machine Learning, artificial Intelligence, Big Data Analytics, Cloud Computing, ChatBots, Wearable Devices, Drone, etc. The aim of discovering all these modern technologies is to improve the quality of life of the common people and make their daily job much easier than ever before. Many business and industrialist have heavily invested in this technologies and they are reaping rich rewards in the recent times. Out of all these technologies, Artificial Intelligence (AI) has raised its standard tremendously in the last 4-5 years.
Source: HOB10575
The best jobs right now in the planet include titles like data scientist, data engineer, and business analyst. Yet too often, employers find it hard to acquire the right person for a job. There is a persisting gap between the skills possessed by the current or the emerging workers and the abilities required by the business.
Source: HOB25455
Modi government has actively used big data and analytics in its governance to succeed and reform the country. Here is a look at some of the top use cases.
Source: HOB15696
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgemental error.
Source: HOB23757
Flipkart the indian online retail giant is on a hiring spree and looking for data scientists actively in order to further their AI in India program.
Source: HOB15993
Marketing in today's world is however much more complex, and organisations are leveraging the power of technologies and we as a marketer are ask to sits through all the voice and figure out the best marketing strategies and always in a limited budget. Hence, SMAC Stack is the new wave of computing that will drive high customer engagement, greater innovation and exponential growth opportunities with minimum cost.
Source: HOB15153
All have probably heard the buzz, there is a big bet on Machine Learning and Artificial Intelligence let's jump to the discussion that how Machine Learning is shaping Digital Marketing and most of the organizations are leveraging the power of Machine Learning technology.
Source: HOB19377
Deep Learning is constantly evolving at a fast pace. New techniques, tools and implementations are changing the field of Machine Learning and bringing excellent results.
Source: Kdnugget27663
A new report aims to help universities shape data analytics education. Technologies that collect data for analysis exist in pretty much every aspect of life - from smart thermometers in homes to wireless sensor networks.
Source: EdTech11934
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgemental error. Data Science is everywhere and here is the rescue for how to be a data scientist.
Source: HOB11949
Data analytics is the key to drive optimal strategy for every business. It helps a business to effectively target consumers with marketing efforts while also creating products that facilitates in solving current problems.
Source: HOB10647
Marketing in today's world is however much more complex, and organisations are leveraging the power of technologies and we as a marketer are ask to sits through all the voice and figure out the best marketing strategies and always in a limited budget. Hence, SMAC Stack is the new wave of computing that will drive high customer engagement, greater innovation and exponential growth opportunities with minimum cost.
Source: HOB15651
Are you currently pursuing your masters in Data Science? Overwhelmed with Buzzwords and Information? Don't know where and how to start your study? Then start with this article and a starter kit provided, but learn it for excellence and not just for the exams.
Source: Kdnugget17358
All have probably heard the buzz, there is a big bet on Machine Learning and Artificial Intelligence let's jump to the discussion that how Machine Learning is shaping Digital Marketing and most of the organizations are leveraging the power of Machine Learning technology. Machine learning has become even more sophisticated and accessible and the industry is seeing rapid growth in ML marketing solutions. This efficiency in identification and classification is at the heart of marketer's attraction to machine learning. As marketers are faced with unprecedented amounts of data, they need solutions to quickly analyze and deliver optimal digital communications.
Source: HOB11169
Technology is making financial services, particularly lending, one of the most enthralling segments to keep an eye on. While several technological transformations going on, here below are two which are already in flourishing mode and ready to completely change the way financial sector services are offered online.
Source: HOB13764
Data analytics is the key to driving optimal strategy for every business. It helps a business to effectively target consumers with marketing efforts while also creating products that facilitates in solving current problems. Businesses are using data analytics in various aspects within technological tools across departments, from IT management to customer support administration. By storing data safely and securely in a cloud-based backup system that uses file encryption, enterprises can protect private consumer information and business insights that provides them with a competitive edge.
Source: HOB8415
Big data analytics is the process of examining large and varied data sets -- i.e., big data -- to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. Their effectiveness depends on the collective use by enterprises to obtain relevant results for strategic management and implementation.
Source: Maruti Tech Labs25662
Is data analytics fuelling the IoT revolution or is IoT fuelling data analytics revolution is a key question that businesses must look for. These two areas Data Analytics and IoT have a symbiotic relationship. One feeds on the other for growth and adoption. IoT connects all manner of endpoints, unraveling a treasure trove of data. The availability of this data is driving opportunity for data analytics by extracting and presenting useful information for decision makers to make informed decisions, which are more predictive in nature rather than reactive.
Source: HOB9288
Social media analytics applications gather data from social media websites and analyze it further using analytics tools to carry out business decisions. For the marketing professionals, analytics tools are the life sustaining organs as they seem to be one of the simplest ways for them to spot and keep in pace with what is happening in the digital world.
Source: HOB13986
SINCE THE CAMBRIDGE ANALYTICA scandal erupted in March, Facebook has been attempting to make a moral stand for your privacy, distancing itself from the unscrupulous practices of the U.K. political consultancy.
Source: HOB14235
There is no shortage of hot takes regarding the significant impact that artificial intelligence (AI) is going to have on business in the near future. Much less has been written about how, exactly, companies should get started with it. In our research and in our book, we begin by distilling AI down to its very simplest economics, and we offer one approach to taking that first step.
Source: HOB14418
Big data isn't just a buzz word anymore. It is extremely important for organizations to pay attention to it. Data is now driving more organizational decisions than ever before. With vast amounts of data being produced in real-time, there is a huge demand for people with skills to manage, analyze and help organizations use this data effectively. Technology changes frequently, and so do buzzwords. Big data, which was one of the most used terms until recently, has been replaced with 'real-time'. This doesn't mean that the demand for big data skills is now low. Rather, it simply means that the keyword has been replaced.
Source: HOB16128
If you aren't using social media as a small business owner, you are missing out on valuable customers and inexpensive marketing. Using social media, your social media marketing campaigns have the potential to reach a lot of people. "Social media provides targeting capability, as well as reach and scale, at a lower cost than almost all other marketing channels," People are on social media all day, every day brands must go where the people are
Source: HOB13839
The practice of data science requires the use of analytics tools, technologies and languages to help data professionals extract insights and value from data. A recent survey by Kaggle revealed that data professionals relied on Python, R and SQL more than other tools in 2017.
Source: HOB24600
According to Forbes, 53 % of organizations are embracing Big Data Analytics, which means the need to gather and secure data has never been this critical before.
Source: HOB14748
Big data is the major field in IT that is going to change many trends in the industry. Their individual applications are ginormous and will start a new era in the technological world. Most companies already understand the importance of using big data to drive insights and decisions and this is already on hype.
Source: HOB9321
Today, big data has made it possible to reap immense benefits for businesses, right from sales, to marketing and accounting, and almost everything. Human Resources (HR) is not a business function that comes to our mind when we think about big data, but it is a business function that can acquire huge benefits.
Source: HOB9741
Teradata Corporation is a provider of database-related products and services. Putting all the infrastructure in place needed to drive real-time insight is a complex endeavor. The number of individual platforms that need to be stitched together is often daunting to even the most experienced IT organizations. Looking to make it simpler to achieve that goal, Teradata announced it has combined support for geospatial, temporal and time-series data into a Teradata Analytics Platform that can be queried using Python, R, SAS, or SQL-based tools.
Source: HOB9495
How do you combine historical Big Data with machine learning for real-time analytics? An approach is outlined with different software vendors, business use cases, and best practices. Big Data has gained a lot of momentum recently. Vast amounts of operational data are collected and stored in Handoop and other platforms on which historical analysis is conducted. Business intelligence tools and distributed statistical computing are used to find new patterns in this data and gain new insights and knowledge for a variety of use cases: promotions, up- and cross-sell campaigns, improved customer experience, or fraud detection.
Source: HOB11304
According to an IDC Digital Universe Study, by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet. Uncovering insights from this homogenous amount of information will require the seamless adoption of big data technologies, stronger data security, and integration of AI, machine learning and cognitive technologies applications with business operations
Source: HOB13683
No matter how large or small a company is, organizations across the globe generate a massive amount of data. While businesses have quickly come to realize that there is tremendous value to be extracted from the large volume of data that is collected, they are still not harnessing the opportunities that can be derived from analyzing data properly.
Source: HOB10197
Today, we live in a world which is highly driving towards digital transformation. Digital Transformation is more than just a buzzword - it's a process of using technology to radically change your business.
Source: HOB9276
NEC Corporation (TSE: 6701) today announced the establishment of dotData, Inc., a new startup company based in Cupertino, California, in the heart of Silicon Valley, that develops and globally provides software that automates data science processes using artificial intelligence (AI).
Source: HOB12939
The amount of digital data in the universe is growing at an exponential rate, doubling every two years, and changing how we live in the world. Big Data is surely a big deal. We definitely are seeing an increase in activity with companies responding to the impact big data has made on their business.
Source: HOB8946
It seems like data/analytics has much less clarity around roles than most other common functions at tech companies. Do you think this will ever change? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.
Source: HOB10404
As more and more Indian firms look to leverage big data for various aspects of their businesses, data science and analytics professionals are having their day in the sun.
Source: HOB17772
Big Data can deliver remarkable marketing campaigns however, the success of the campaign will depend upon the enterprise's willingness to invest in technologies, processes, and its engagement with customers. Many consider marketing as an art nowadays, and it is, beyond doubt, a complicated piece of work, which requires craft as well as graft. Going back to the website's blunder, it is evident that there was a terrible misinterpretation in the analytical data they received. Today, direct marketing heavily relies upon Big Data analytics to pin down individuals based on their Google queries, browsing history, credit card swipes and so on.
Source: HOB9090
Big data is growing everyday and becoming a very popular word in the tech world. Many people around us keep talking about it, but do they know what it actually means? Big data is nothing but the collection of unstructured data. This data is not in a particular format and because of this its datasets sizes are generally huge measuring tens of terabytes and sometimes crossing the threshold of petabytes. The term big data was preceded by very large databases (VLDBs) which were managed using database management systems (DBMS). Having so much of data pertaining to the business provides a very niche way of increasing the sales or profits of any company. But in order to do so we need to make use of Big data analytics.
Source: HOB9027
Machine learning has been instrumental in solving some of the important business problems such as detecting email spam, focused product recommendation, accurate medical diagnosis etc. The adoption of machine learning (ML) has been accelerated with increasing processing power, availability of big data and advancements in statistical modeling.
Source: HOB12207
Data has always been important for businesses, but the importance of information analytics have been discovered only recently. However, generally some people confuse information analytics with big data or other data tools, and think that accomplishment required for data assemblage are same as the skills required for data analytics
Source: HOB8841
Big data is now playing a large role in most industries, with the number of uses for information rising regularly as new algorithms and methods to analyze data are developed. The application of big data in taxation has eased the effort required for high levels of accuracy, and has increased the uses for tax information around the world. Big data in public administration has yet to play a significant role across the industry, however, its potential awaits untapped.
Source: HOB12810
For any company, ability to analyze, access and manage big amount of data is critical to ensure successful operations. Companies are increasingly looking for ways to reduce costs of using large data while optimizing the value of big data available.
Source: HOB14799
The use of data analytics is becoming more prevalent in the current business landscape. Legal department business models are changing. They're operating more like business units within the corporation and are expected to be high performing and successful.
Source: HOB51165
In recent years, Data Analytics have become a buzzword for every business organization as information is the crucial resource for any organization which can provide a competitive edge to the company.
Source: HOB16104
Analytics has become almost an integral part of any organisation process. It has wide scope in improving decision-making ability, efficiency and growth of the org. In marketing and sales, Some company use data analytics as a tool to enhance efficiency of sales team, increase customer base, generate more revenue and ensure Customer loyalty. However most of the company are still not actively involved with it.
Source: HOB15351
Facebook introduced new analytics features including a creature to track customer journeying through multiple channels on Tuesday at its F8 developer conference. Journeying is the most notable addition to Facebook s currents analytics peter. It provides omnichannel data and reporting, so marketers can see what exploiter are doing right before they take an action that results in a changeover.
Source: HOB10929
Big data can transform how decision-makers view business problems and inform strategic decisions, allowing them to rely upon objective data. Good data, sound analysis and valuable insights are critical for mitigating risks, making balanced strategic decisions and competing against others.
Source: HOB35487
In 2018, data and data analytics can't be ignored. Data Analytics is quite big buzz these days. Analytics is the combination of analysis and logics and it is the collection, measurement, analysis, visualization and interpretation of digital data illuminating user behaviour on websites, mobile sites and mobile applications. Following are the six ingredients of a successful digital analytics transformation.
Source: HOB9012
Today, organizations acroos the world are leveraging the power of big data in everything, right from designing workplace policies to social media recruitment. Big data has become a buzzword in business circles today. Big data can help a lot when it comes to talent acquisition.
Source: HOB12228
More businesses and organizations are using data analysis tools, thanks to the explosive growth in the ground of data analytics has seen in recent years. With data analytics, and the kind of outputs expected from it, there are questions growing about the trust that is placed in it, and the fresh ways of decision making.
Source: HOB8778
With the increase in generation of data, companies are bombarded with large amount of data. This forces company to move towards data-driven approach to business.
Source: HOB11484
With the growing amount of data available with the organization, Data analytics becomes an integral part of almost every business management. Analytics in itself has wide applicability to add more value to the business
Source: HOB12363
Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data has been a crucial part of our lives.
Source: HOB19071
In 2018, data and data analytics can't be ignored. Data Analytics is quite big buzz these days. Analytics is the combination of analysis and logics. Analytics can't be performed without software's. By applying data analytics we can draw conclusion about the any given set of information.
Source: HOB17820
Analyzing the great potential of Big Data in health care industry, Doctors, Researchers, Scientist and other stakeholders are trying to real world evidence to influence their decision making. Healthcare industry is experiencing a rapid movement towards a new world where focus will be on value and outcomes.
Source: HOB7695
Analyzing the great potential of Big Data in health care industry, Doctors, Researchers, Scientist and other stakeholders are trying to real world evidence to influence their decision making. Healthcare industry is experiencing a rapid movement towards a new world where focus will be on value and outcomes.
Source: HOB9345
Manufacturing is important part of the world's economic development, but the roles it plays in advanced and developing economies has shaped dramatically. In developing countries, manufacturing operations bring new employment opportunities that are changing the societies. Manufacturing always remains important as a job initiator in the whole world.
Source: HOB11673
The digital transformation and advancement in technology continuously pushing organisations to adopt new technologies. As consumer and marketer both are getting empowered with the development in technology, A marketer cannot afford to miss single opportunity to increase customer overall experience.
Source: HOB13770
Predictive Analytics is a buzzword today. Wondering what is it? It's Applications? So, first of all, let's get started on the meaning of Predictive Analytics.
Source: HOB29379
Telecom sector is one of those industry which always looks for new trends and innovative technology to provide better services to its customer. Telecom Industry has already using the trending technologies such as AI, Chatbots, Machine Learning but the development in AI will be a turning point in terms of connectivity, communication, efficiency and delivering customer services.
Source: HOB14295
When machines are connected to internet, we start getting real-time data in large amount. That real-time data is not only helpful in the Descriptive analysis but also helpful in understanding the behavioral patterns to get predictive and prescriptive analysis which means what will happen and actions we have to take. In short, with the emergence of IoT, the whole equation has transformed. Now we can leverage this data in our daily job to get best possible outcomes and also understand where their time and money are spent. So that we can use the resources in an effective manner hence wastage can be minimized.
Source: HOB16356
With the growing awareness about big data and data analytics, it has revolutionized many industries. Logistic is another field which is going to see transformations with the application of big data analytics in its process
Source: HOB5463
With the growing awareness about big data and data analytics, it has revolutionized many industries. Logistic is another field which is going to see transformations with the application of big data analytics in its process.
Source: HOB14772
Now a day's mobile became the central part of everyone's life. This shows marketer to exploit mobile generated data to deliver delightful experience to their customers. The connectivity through the mobile devices using different mobile apps can tell more about consumers' needs, expectations and behaviors.
Source: HOB14022
Extensive list of 50+ APIs in Face and Image Recognition ,Text Analysis, NLP, Sentiment Analysis, Language Translation, Machine Learning and prediction.
Source: HOB23124
From data driven strategies to decision making, the true worth of Big Data has been realized, and has led to opening up of amazing career choices. Check out these 12 interesting careers to explore in Big Data.
Source: HOB19446
The shift towards data driven approach has created demand for data analyst. The application of big data and data analytics is increasing day by day. So, career in data analytics will provide students with opportunity in different industries.
Source: HOB8280
The transformational shift in HR functions from routine matter to strategic function has changed the role of HR manager from supporter to strategic adviser or business partner. With this shift, companies have understood that human resource is central resource.
Source: HOB9579
Artificial intelligence (AI) and machine learning are transforming the global economy, and companies that are quick to adopt these technologies will take $1.2 trillion from those who don't.
Source: HOB14142
Increased user base on digital channels, growing awareness of big data and implementation of data analytics are elevating marketing efforts and its impact on bottom-line. Now, smart marketer use predictive analytics to their grow business.
Source: HOB8001
Part four of my ongoing series about building a data science discipline at a startup. You can find links to all of the posts in the introduction.
Source: HOB13560
The business leaders are investing huge amount in analytical tools, data scientist and data analysts. Still they are not gaining added value in business. Implementation of advance analytics is not proving them scalable solutions.
Source: HOB8031
Data-driven approach became one of the important feature of modern business organizations where analytics is the key strategy for competitive and sustainable business growth.
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Cynthia Saunders-Cheatham is a senior careers director at Johnson at Cornell. She says more employers want MBAs with data analytics skills
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Artificial intelligence and machine learning is no more hype. These technologies are changing our life, the way communicate, the way we do business and the way we live. We can say many examples where AI and machine learning has transformed our daily life.
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It also brings out the fact that India currently contributes about 10% of the open job openings for data scientists globally, making it the largest data science hub in the world outside the U.S.
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The game today is no longer just about products and services, but end to end customer experiences. Great experiences create loyal customers and competitive advantage. We plan strategies for customer loyalty programs or customer retention, but at the same time we forget that loyalty is a sentiment. The planned strategies can only worked if our customers have any kind of sentiment towards our offerings. If it's good, it can be bettered, if it's bad it can be remedied. But the main thing is that, what do your customers feel about you?
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If ever there was a gold rush for data scientist jobs, India would be ground zero - or almost.
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Customer survey is the primary source of deriving customer feedback for many companies, despite the growth in embracing of other customer feedback sources like social media, call center conversations and emails. It usually contains structured questions, requesting customers to rate their level of satisfaction with their experience. Two common customer surveys are relationship and transactional surveys. The main difference between these two surveys is that relationship surveys measure attitudes about the experience and transactional surveys measure attitudes in the experience. These approaches of the survey are used to help businesses to improve the both strategic and tactical decision-making power.
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Now big data and analytics lies in the heart of every organization but data will act as a garbage for data scientist until and unless they are not able to visualize the data and its impact on key activities and the business outcome.
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The revenue of India's analytics and business intelligence (BI) software market will reach $304 million in 2018, an 18.1 per cent increase over the past year, according to a Gartner forecast on Tuesday.
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In retail business there is some form of typical competition that has been evolved from an longer period in business .The retail business is to identify the needs of the customers in which the best sales can shine out among the competitors . The response of every business folks is to analyze and make comparison to other businesses in your industry. Find if there is something useful to the customers as well as to your business and the good response is to define your brand and consistently communicate your own Unique Selling Proposition. This blog will gives you the 5 strategic ways through which you were able to beat the competition and also remain in business strong and lucrative.
Source: Roosboard18636
Technology revolution all over the world are changing the business landscape and making the world more competitive. The data is growing exponentially and the only way to survive is to exploit data intelligence and analytics.
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Indian is an agrarian economy over 58 percent of the rural households depends on agriculture as their principal means of livelihood. Agriculture activities like planting, maintaining and harvesting crops need money, energy, labor and resources so diminish and switch some of the human actions and guarantee efficiency that why the AI comes into the picture. The big company Microsoft is taking AI in agriculture a further step and helped Indian farmers to begun use of AI to increase efficiency and further encouraging them to harvest a good crop.
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Indian Navy is planning to incorporate big data analytics and artificial intelligence into their operational functioning of the forces. In the conference of the commanders they reviewed the Navy's "Mission Based Deployments". The purpose of the review is at maximizing benefits ensured from the deployment of Indian Navy ships and aircraft to the dangerous areas within the Indian Ocean Region.
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Inditex, the world's largest clothing retailerand owner of Zara stocks up on Artificial Intelligence, Big Data and analytics into its business strategy to stay ahead in the race of competition. The biggest fashion retailer is hooking up with tech companies and hiring talent from startups and partnering Analytics and investments, which offers an AI-powered consumer behavior forecast platform.
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Big data is used to identify patterns and trends that can yield powerful insights into human interactions majorly consumer behavior. The data includes demographic, geographic and psychographic attributes collected from diverse sources throughout the consumer cycle as well as from the other field of the individual's life.
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Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data science and data analytics, people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. However, although they may sound similar, the terms are often quite different and have differing implications for business. Knowing how to use the terms correctly can have a large impact on how a business is run, especially as the amount of available data grows and becomes a greater part of our everyday lives.
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In 2018, data and data analytics can't be ignored. Data Analytics is quite big buzz these days. Analytics is the combination of analysis and logics. Analytics can't be performed without software's. By applying data analytics we can draw conclusion about the any given set of information.
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Leveraging the application of big data, whether it is to improve the process of product development, improve customer retention or work through the data to find new business possibilities organizations are more relying on the expertise of data scientists to sustain, grow and beat their competition. Consequently, as the market for data scientists increases, the system presents an exciting career path for students and existing professional.
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For all those who are searching for job, year 2018 is going to be the year where you can move further in the tech industry and here is the list of top 10 highest paying jobs.
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A guide to making the most out of your data.
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No,but if you have some knowledge about data mining algorithms. That will be beneficial in learning data analytics. Data Analytics is a field demanding a variety of skills. Having knowledge of Hadoop is one of them.
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Having done training and mentoring for quite a while, I noticed something that is not taught in most data science curriculum that I have come across but in my opinion, its an essential business knowledge that the data scientist need.
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Analytic is the interpretation of the data collected. Raw form of data is not of any use. It is important to convert raw data into analytic so that it is easier to find that what is the decision that are to be taken by the use of analytic. Businesses use this analytic for making actionable business analytic that will help them in taking real time actions.
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Data Analysis and data analytics are often treated as interchangeable terms, but they hold slightly different meanings. Data analysis is the overarching Data Analyst practice that encompasses the use of data analytics tools and techniques to achieve business objectives
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Big Data
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Aviation Industry is on radar next and it bets on Big Data Analytics. This industry needs to move beyond its present way of working so big data analytics is only key to unlock the potential.
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The growth of data is not going to stop. This will usher in new challenges and opportunities. Below you can find the five hottest big data trends for techies and business.
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Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
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The retail industry traditionally has been generating detailed data on consumer behaviour and purchase history through various transactional and customer relationship systems. Exploiting these data to increase basket value and optimize margin remains a challenge with traditional technologies of business intelligence tools and data warehouse architectures.
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AI has gained its popularity in many industries and in various fields as well. It is also going to impact market research and its audience. AI also helps marketers to gain insights about the data that has been already collected.
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Google Cloud announcements bring deep learning and big data analytics beyond data scientists, but enterprises will want more.
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Data Scientists are big data wranglers. They consider mass and messy data both structured and unstructured and use their formidable skills and organize them accordingly. They use or apply their analytics power to uncover hidden solutions to business challenges.
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The skills that have remained important are (a) understanding the fundamentals of statistics, optimization, and building quantitative models and (b) understanding how models and data analysis actually apply to products and businesses.
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The ever-improving capabilities of big data platforms increasingly create new opportunities for industries with representatives who want to examine analytics to benefit their companies.
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Data Scientists is the highest paying and demanding job in the current year. All HR professionals are under pressure to get hired the best data science talent so they can achieve the valuable business insights. According to Harvard Business Review described the role of data scientists as it is the sexiest job of the 21st century.
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IoT has already created the hype in the business world. Keeping security and occasional performance issues aside, IoT has already created more productive environments in the business by the year 2025, its direct economic impact on retail, manufacturing, healthcare and other important industries.
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According to the report, global dark analytics market was valued at around USD 193.65 million in 2017 and is expected to reach approximately USD 928.58 million in 2024, growing at a CAGR of 25.10% between 2018 and 2024.
Source: Zion Market Research5574
Computers are always been quicker than humans at consuming, calculating and computing data and artificial intelligence have benefited a boon for our global economy. Combining insights from computer science with cognitive science can advance human thought, shape outcomes in ways that transform the process of human capital development and enhance overall employee contributions and engagement.
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Here we get to know that how companies can use systems of insights platform to improve the data sourcing, analysis and insights and how they are managing their data. Recently TIBCO has also published a webinar on know the answer of this question. According to director of analytic strategy, Shawn Rogers that how closed-loop SOI platform offer a continuous learning solutions. All the experts are always in search of getting good or valuable data so that they can get best from that by using their analytical skills.
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Significantly every industry is finding a way to benefit from AI-driven analytics. While great strides have been made in the adoption of real-time analytics in the marketplace, artificial intelligence could ramp this up. We have analyzed along the way with analytics in recent years, in which data is applied against algorithms or analytics engines to determine what it may mean to the business.
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From a very generic perspective it does not matter how small or big the company is, it depends on the amount of data the type of data and how are they using the data. As per the recent trend, the need to handle with large amount of data is increased. As per the business requirements we are not able to achieve 100% accuracy when we are dealing with normal data conversions.
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Sometimes you open a big Dataset with Python's Pandas, try to get a few metrics, and the whole thing just freezes horribly.
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When you think of the perfect data science team, are you imagining 10 copies of the same professor of computer science and statistics, hands delicately stained with whiteboard marker? We hope not!
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Data Science, Machine Learning, Artificial Intelligence and data analytics are quite buzzword. No doubt these technologies will transform all the industries but most likely the technology that will change our profession in the short run will be Robotic Process Automation (RPA).
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The growth and success of the organization totally depend on your ability to collect good amount of data, managing those data which leads into business insights and outcomes. Data is all around only matter is that we have to collect good structured data which is further helpful for the organizations.
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Machine learning is having a huge impact in almost all the industries. From Google brain to self-driving cars all are made using a machine learning algorithm. It is currently growing and expanding rapidly and more and more people are learning it.
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I was listening to an old episode of Partially Derivative, a podcast on data science and the news. One of the hosts mentioned that we're now living in the "golden age of data science instruction" and learning materials. I couldn't agree more with this statement. Each month, most publishers seem to have another book on the subject and people are writing exciting blog posts about what they're learning and doing.
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Nowadays, there is a huge list of powerful data visualization tools to help you illustrate your ideas, visualize your data, make it talk, share your significant analytics with customers and the global community.
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I recently had the chance to use machine learning to address an issue that is at the forefront of the American media, the difficulty of recognizing fake news.
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At the moment of writing this post about Data Analytics and Data Science, I am bootstrapping a data literacy consultancy, catering to large enterprises around the globe.
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Big Data Analytics is the perfect solution for the complex problems. Every marketer have to take right decision for their organization and now for all those decisions they need not to be depend on their employees. With the help of big data analytics they can easily come to know about each fact and findings.
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We have covered all the courses at a beginner level. As i have classified these courses on the basis of difficulty level. Here we have come up with 200 online programming language and computer science courses at an intermediate level.
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Modern data science emerged in tech, from optimizing Google search rankings and LinkedIn recommendations to influencing the headlines Buzzfeed editors run. But it's poised to transform all sectors, from retail, telecommunications, and agriculture to health, trucking, and the penal system.
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Despite the struggles, it is possible to leverage data science and machine learning to scale your business, save time and grow revenue while improving your customers' experience.
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As data science and big data get the hype in the industry, handling it is a challenge we need to deal with. Along with all the pros on one side keeping yourself advent with the latest improvements in this field is another issue which bothers us.
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What do data science, data analytics, and business intelligence mean at Grab and how are they being used? - Wong Mun
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The Tech Companies are hiring for various positions in India and abroad for Data Science, Artificial Intelligence, Machine Learning. Know the eligibility criteria, job location, and profile. Find out what all is needed to work with the biggest tech-giant in the world
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Data analytics is becoming more vital for businesses, and data scientists are in high demand. But the emerging field is broad, and some companies say they have struggled to find job candidates whose skills fit their needs.
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Social Media data is the new gold and analytics for the businesses. Social media analytics is an amazing art and science of extracting valuable hidden business insights from the platform called social media.
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With data sciences being the focal point, Entrepreneur India analyses why this new trend is now the essential tool for a majority of smart entrepreneurial solutions.
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Chatbots can open the doors of endless business opportunities providing the compelling writing and the visuals. They can effectively deal with every aspect of branding while offering a competitive edge to entrepreneurs and leads to higher productivity.
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A collection of Big Data trends to familiarize yourself with, covering IoT Networks, Artificial Intelligence, Predictive Analytics, Dark Data and more.
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In today's world, whatever your job, having skills and knowledge in Data Science will play a huge role in your career development. For example, big data and analytics gathered from customers allow marketers to build more effective digital marketing campaigns.
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Understanding data is key to unlocking job opportunities - Harvard Gazette. New course hopes to give students an edge in the job market.
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Data Scientist is the very demanding role in every big organisation and they have power to unlock the hidden values in the data's. They are very good at data handling and manages data at a very huge scale.
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There are several ways companies can alleviate the pain and accelerate the data science transition, particularly as it relates to the IT department.
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What are the most to least important skills, and the types of people who apply for data science jobs. I talked about all of the skills I want in an ideal candidate. But since that candidate doesn't exist, I have to prioritize what attributes the candidates that I hire have.
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The artificial intelligence (AI) industry has been leading the headlines consistently, and for good reason. It has already transformed industries across the globe, and companies are racing to understand how to integrate this emerging technology.
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I started off by doing online courses for Data Analytics that were either free to access or available at a small cost, all of which were very focused on certain topics of the Data Analytics field.
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The big data analytics technology is a combination of several techniques and processing methods. What makes them effective is their collective use by enterprises to obtain relevant results for strategic management and implementation.
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People often ask me How can I learn Data Analytics? and I often stumble upon this question How to become a Data Analyst on Quora too. The answer is pretty much clearly available all over the internet. The actual issue is not how to become a data analyst but it is if we are ready to become one?
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Regardless of where you stand on the matter of Data Science sexiness, it's simply impossible to ignore the continuing importance of data, and our ability to analyze, organize, and contextualize it.
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Machine Learning is the term which we have been Hearing Now everywhere. When I Started My ML Journey Back in April 2016 I was like complete Noob having No Idea what ML is I used to Think does ML means that Machine are learning ?
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All marketers are familiar with the value of monitoring and analyzing web data and analytics. Most of the organizations are using Google Analytics to know the facts and figures of the organization. All extracted data leads to the efficiency, revenue growth and success of a business.
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Why Data Analytics? To answer this question, you need first of all few clues about my background. I am Rachid Oukhai, founder of Upsilon, Peculium (Data).
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In today's world with the introduction of "Internet of Things" and the improvement of "AI Technology" has led to implementation of big data solutions to almost every organization whether small or large organizations. With the help of big data analytics the management can easily take the decision and improve their operational efficiency.
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Sometimes you open a big Dataset with Python's Pandas, try to get a few metrics, and the whole thing just freezes horribly. If you work on Big Data, you know if you're using Pandas, you can be waiting for up to a whole minute for a simple average of a Series, and let's not even get into calling apply.
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Survey of company leaders shows the vast majority are planning to hire data scientists as economic uncertainty continues.
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Artificial intelligence is really invaluable right across the spectrum of space problems.
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Companies are aware with the importance of digital data in businesses. All organizations had already started to understand and identify what valuable data they can possess. So they are collecting it, analyzing it and using it to improve their business and operations. They are leveraging machine learning applications that help them in solving complex hurdles.
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There are lot of online free resources available from where we can get insights and use that knowledge in our daily routine. But here is the collection of good Big Data books that matches in-depth and comprehensive detail for the readers and these books are selected on following parameters like relevancy, popularity, ratings, publish date and ability to add value to businesses.
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The two most powerful technologies Data Science and Machine Learning are not only changing the industries but also influencing many movies-makers across the globe. Basically these technologies are penetrating the entire world.
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Despite my math background, I've always considered myself first and foremost a consumer researcher who uses data analytics to gain insights into human behavior, and that's what I focus on at Farmers Insurance. Today, if you're a small business owner, you need to get that data just as much as any large corporation. And even if you've always been math-averse, you can learn how to apply analytics to your own business.
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In 2018 it's good time enroll for Data Analytics and it can't be ignored as analytics is the combination of analysis and logics. Data informs a large amount of decisions with strong groundwork rather than just taking shots in the dark.
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All data technologies are evolving and getting a lot of hype in the industries. Now most of the organizations are leveraging these technologies ie. Artificial Intelligence, Machine Learning and Data Science. In this article there is a colloection of few artificial Intelligence, Machine Learning and Data Science start-ups in India.
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Data is not for only Analytics team now as Data Scientists are in demand and data covers all most many roles in an organization and employees need the literacy to handle it effectively. Now in most of the organization the data skills matters a lot because data is gold for all the industries and it is in very huge numbers as well.
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Predictive Analytics is a buzzword in today's technical world. Data is in huge quantity and it is very hard to manage those data so predictive analytics come into the picture. Wondering what is it? So, firstly we should start with the meaning of Predictive Analytics that what exactly it is.
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Predictive Analytics is a buzzword in today's technical world. Data is in huge quantity and it is very hard to manage those data so predictive analytics come into the picture. Wondering what is it? So, firstly we should start with the meaning of Predictive Analytics that what exactly it is.
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Predictive Analytics is a buzzword in today's technical world. Data is in huge quantity and it is very hard to manage those data so predictive analytics come into the picture. Wondering what is it? So, firstly we should start with the meaning of Predictive Analytics that what exactly it is.
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Data Science is a very huge field and it allows fresher and experienced professionals to kick-start their career in this evolving field. Now HR of the companies are seeking for Data Scientists CV and ready to pay the highest salary. For this most of the people are struggling to get learn about data science.
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My Mario Kart reflexes aren't what they used to be, but I am better at data science than I was as a fourth grader, so in this post, I'll use data to finally answer the question "Who is the best character in Mario Kart?"
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Data analytics is the primary enabler to derive insights and reach out to meaningful truth, resulting in business growth and increased revenue.
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Technology Business Research (TBR) recently come out with a report and its headline is, "Winning The Business Of Digital Transformation Services Requires A Process-Led Approach" authored by Sebastian Lagana and Jennifer Hamel. The report is full of good nuggets, but what all professionals especially liked the way that they categorized the 3 phases of Digital Transformation in his report:
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There is no more field left by Data Science as with the help of Data Analytics the medical science will move to the new level from computerizing medical records to drug discovery and genetic disease exploration. Data Science and medicine are continuously developing and it is important that they both will advance together.
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There is no more field left by Data Science as with the help of Data Analytics the medical science will move to the new level from computerizing medical records to drug discovery and genetic disease exploration. Data Science and medicine are continuously developing and it is important that they both will advance together.
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Top 100 Data Science Resources & Tools For 2018 Whether you're just getting started in data science, or are gearing up to get a Masters in Data Science or Business Analytics, there's always more to learn. This guide gathers 2018's top data science resources on the web for learners of all stages.
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Deirdre Dempsey has decades of experience dealing with data analytics, data science stemming from a strong foundation in mathematics.
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If you want to become more data driven than you should have good understanding of all the languages and you're supposed to be master in Data Science field as well. Building the first data project is actually not that hard only you should know the basic steps and categorize them from raw data to building a machine learning model.
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Machine learning offers organizations the potential to make more accurate data-driven decisions and to solve problems. Now organizations are leveraging the machine learning technology and this is not the magic it presents many of the same challenges as other analytics methods.
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Mention the word "search" to most laypeople and it conjures images of Google and Bing. Mention it to most data scientists and it usually conjures notions of keywords and text retrieval, and maybe a passing reference to open source projects like Elasticsearch, Apache Solr, of they are particularly well-versed-Apache Lucene.
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For Data Scientists, mistakes help them become sharper and discover new data trends, but that doesn't mean mistakes in Big Data Analytics are not sometimes quite problematic.
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A collection of useful mobile applications that will help enhance your vital data science and analytic skills. These free apps can improve your listening abilities, logical skills, basic leadership qualities and more. Data science and machine learning are evolving with their abilities to transform the world around you.
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It is crucial to ask the right questions and/or understand the problem, prior to beginning data analysis. Below is a list of 20 questions you need to ask before delving into the analysis
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According to IDC, global spending on Artificial Intelligence (AI) and cognitive systems will reach $19 billion by 2018. This is an increase by approximately 54% over the total amount consumed in 2017. Mergers and acquisitions are constantly taking place. 2017 alone witnessed some huge acquisitions like Yahoo was acquired by Verizon, Apple bought Shazam etc. Top consulting company Deloitte predicted that technology acquisitions will accelerate mergers and acquisitions in 2018.
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A Data Science primary survey was conducted in August through September 2018, where 961 current and past Data Science students from 18 cities in India gave opinions on data science courses they attended.
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Business Analytics is more suitable for folks who enjoy work which will involve leveraging both business and technical skills in order to create value for the clients. On the other hand, Data Science is a little bit heavier on the coding and technology. During the interview process for Data Science courses, you can expect to be grilled much more on your coding skills as compared to a Business Analytics program.
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Once the Business Intelligence reports and dashboards have been prepared and insights which are extracted from them, this information becomes the basis for predicting future values. And the accuracy of these predictions lies in the methods used.
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Big Data visualisation is among the utmost important components of working with various Big Data analytics solutions. Once the flow of raw data is represented with images, decision making becomes much easier. In order to meet and exceed the customer's expectations, the tools for Big Data visualization should provide a certain set of features.
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Analyzing data has become an essential part to leverage business significantly & gain a competitive advantage. Research says organizations that rely on big data-driven business strategy can gain insights faster for reducing costs and increasing revenue. Top brands like Intel has successfully made use of these from top big data analytics companies to analyze their data for advanced marketing & huge savings.
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Check out five of these actionable intuitions you can learn from Google Analytics and see how you may be able to apply them to improve your SEO.
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So here is the difference between a website and a web-enabled application. It is pretty easy but difficult too as a website is related to a particular page and web app is a portal where you get all the content and the information and you can easily view the web apps through browsers.
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Here are 4 main reasons data scientists may become dissatisfied with their jobs. Data professionals choose the career path of data science for the complex problem solving, the cool new machine learning algorithms and the expected impact their work will have on real business problems. However, this is often not the case.
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In recent years, the ability of data science and machine learning to cope with a number of principal financial tasks has become an especially important point at issue. Companies want to know more what improvements the technologies bring and how they can reshape their business strategies.
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Since the inception of computers, scientists have had a strong desire to make machines understand the human language. Communicating like a human is a big ask for a robot. Natural Language Processing. NLP has been around for a while, but as of late, has benefited from recent developments in Machine Learning and Deep Learning techniques. Machine Learning is a subfield within Artificial Intelligence that builds algorithms that enable computers to learn to perform tasks from data instead of being explicitly programmed.
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As cyber threats continue to evolve, big data and machine learning are increasingly necessary for a strong cyber security strategy. Will Cappelli, vice president of research at Gartner, says that companies are combining big data and machine learning capabilities as part of a more powerful approach to cyber security.
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It's very common for a customer to see advertisements for products that they may have recently searched for, but also sometimes the marketing emails and pop-up ads are not necessarily suitable with the consumer's interests and may come across as more annoying than actually useful.
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Various business trends today, such as the use of artificial intelligence and multimedia visual marketing, are connected to the concept of Big Data. Every action internet users take generates a data trail, and the amount of machine-generated data is growing too.
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You're probably aware of this by now: data science and data analytics are the skills to have in this day and age.
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Organizations combine vast amounts of information from several sources some public, some proprietary, some from human activity, some from devices to gain unique insights about human behavior and decisionmaking.
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Data mining is sifting through all of the data collected by a business or organization, searching for relationships so that reasonable predictions can be made with regard to behavior. This kind of activity is most common among businesses that deal with consumer behavior of any kind.
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Data scientists, data analysts, and data engineers are in high demand. Here are the big data and data analytics certifications that will give your career an edge.
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Data scientists, data analysts, and data engineers are in high demand. Here are the big data and data analytics certifications that will give your career an edge.
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Social media is just the opposite what it tried to present, as said, leaving everything behind social media didn't come to a period of beating the news behind in any way.
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Machine Learning and Big Data are the two popular terminologies and both are revolutionizing business operations and regularly providing lots of new opportunities. Machine Learning is presently more subject to practical, large-scale applications than it has ever been in past. Big data on the other hand, became a thing in 2013, after it was observed that 90 percent of the world's data was generated in past years.
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If you're someone who is looking to make a move to data science, there are some ways that you can polish your approach to get noticed during your job search.
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Every computer system uses machine learning as it has refined their performance on a definite task. Machine learning is mainly the overview of algorithms and closely concomitant to computers statistics which mainly focuses on predictive analytics. These algorithms are used in many applications, however, they do not work competently with imbalanced datasets. If you have gone through machine learning and data science, you might have faced problems related to imbalanced data.
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The Big data revolution and cloud computing are getting hype and companies are shifting the way they think the way of doing business to incorporate data that will drive their decision-making process. Business models keeps to grow on a constant basis and are presently targeting a system-wide transition based on a data-centric architecture.
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It can't be denied that Big Data is a hot topic in present times. But there are businesses still struggling to shift from concept to execution. The only new thing which allows us to make sense of this information is analytics. The primary goal of analytics is the exploration or application of analytic techniques to large amounts of information in variety of types including unstructured data which comprises of text strings, sound and movie files, documents, images, geo-location data, and documents.
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Cloud Computing is the method to deliver computing services over the internet. These computing services consist of storage, servers, databases, software, analytics and more. Cloud Computing is an information technology which allows the access the shared computing sources with minimal management effort. With the help of Cloud Computing, we can utilize computing resources online over the internet without investing money in building and maintaining computing infrastructure.
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Cloud Computing is the method to deliver computing services over the internet. These computing services consist of storage, servers, databases, software, analytics and more. Cloud Computing is an information technology which allows the access the shared computing sources with minimal management effort. With the help of Cloud Computing, we can utilize computing resources online over the internet without investing money in building and maintaining computing infrastructure.
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Artificial Intelligence, or simply termed as AI, as the name suggests, is the intelligence exhibited by the machines. By acquiring intelligence, although artificial, the machines will become capable of working and reacting like humans. Today, the artificial intelligence that exists is termed as narrow or weak AI.
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Machine Learning is the subset of Artificial Intelligence and all are the part of computer science. It is a data analysis tool that helps us in automating the tasks. Alternatively, it also provides the machines (computer systems) with the capability to learn from the data, without external help to make decisions with minimum human interference. With the evolution of new technologies, machine learning has changed a lot over the past few years.
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How diverse will a lucrative, growing field like data science be in the future?
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To most Americans, the phrase "Medicare Fraud" brings up images of individuals who cheat the system to collect healthcare when they don't need it.
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A new Forrester Research report, Predictions 2018: The Honeymoon For AI Is Over, predicts that in 2018 enterprises will finally move beyond the hype to recognize that AI requires hard work-planning, deploying, and governing it correctly.
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Leadership-capacity constraints are undermining many companies' efforts. New management structures, roles, and divisions of labor can all be part of the solution.
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Data science is basically the application of a combination of mathematical, statistical, analytical and programming skills for the collection, organization, and interpretation of data to allow effective and proper management of the business whose data it is.
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Data mining is the process of examining a data set to extract certain patterns. Companies use this process to determine the outcome of their existing goals. They summarize this information into useful methods to create revenue and/or cut costs. When search engines are accessed, they begin to build lists of links from the first page it accesses. It continues this process throughout the site until it reaches the root page.
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Nowadays every business has big data, and analyzing it has become a significant tool for every business. It changes the way of marketing strategies like how the product is being marketed across various industries. Either it is a startup or a grown up business, every company is considered to be a business of data. In earning the success you need to have data driven strategies which are really needed. if you seem to have fallen in the statistics do not back out, try and collect data to a huge extent.
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While several firms have commenced data analytics initiatives, solely some are victorious. Studies have shown that 70% of data analytics programs fail to understand their full potential and over 80% of the digital transformation initiatives fail. Whereas there are several reasons that have an effect on victorious readying of data analytics, one elementary reason is lack of fine quality data. However, several business enterprises understand this and invest considerable time and energy in data cleansing and remediation, technically referred to as data engineering.
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Technology could be a extremely dynamic field wherever new advancements keep coming back each day. the info is that the next massive factor concerning this contemporary digital age. Entrepreneurs are speedily adopting data-driven methods to power their net presence.
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So how can machine learning help you in building a successful career? Is it possible to have a stable career in machine learning? Few questions trick your mind while choosing your career. But machine learning helps you to overcome as it is an effective tool which has an automatic artificial presence rather than the human mind. Machine learning helps computers to work on their own without any human interaction in this tool. Machine learning also includes multiple learning such as supervised and unsupervised learning and also vast applications. Continuous learning helps you to take multiple and effective decisions at the right time. Machine learning has smart algorithms which are used for the marketing campaigns in many smartphone apps as well as in social media applications.
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Is data literacy necessary in youngsters, the solution is affirmative as a result of data is currently a component of daily life. It's nearly become a responsibility of the typical subject to possess some level of data literacy and understanding. Apparently, this analysis paper argues that young learners have the power to figure with complex data sets if they're supported within the right method and if the tasks are grounded in real-life context.
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Companies that fail to apply data science will be at a competitive disadvantage, according to Deloitte. Here's how to take advantage of new tools, staffing models, and training strategies.
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Now have you ever come across the term data mining? As the name implies, it is an analytic process used to explore a large amount of data in regards to consistent patterns and systematic relationships between variables. Businesses prefer data mining because it aims to predict. Predictive analyses, on the other hand, refine data resources, in particular, to extract hidden value from those newly discovered patterns. �¢??Data mining + Domain knowledge =>Predictive Analytics =>Business Value�¢??
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The common thread all told these examples is edge computing. Outlined by analysis firm Gartner as merchandise that facilitates processing at or close to the supply of information generation, Ed Fowler, vice chairman and head of digital engineering services in Europe, the center East and continent at Virtusa, says businesses ought to care regarding the idea. Why? The speed of results from edge-compute applications is immensely above ancient architectures and this may lead to revenue-making opportunities, price efficiencies, and higher services.
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Another challenge develops when businesses gather data and organize it without considering the questions they will be used when processing the data. Each step in the data collection process should lead toward gathering useful data and analyzing it with the goal of developing actionable Business Intelligence.
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Competitive markets have increased and faced by the media and entertainment companies. There are several ways which can easily bring upon the content of the consumer, operate the need where the operation is done in a better way and more efficiently than ever. Delivering that content means generating more and more revenue they need. Sectors like media and entertainment always deal in data, as it is already known. So is there something new in it?
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I believe leaders have a fiduciary duty to protect sensitive company information. To that extent, risks of data breaches must be managed and mitigated, as they can seldom be completely eliminated. Keeping information available, confidential and integral is the everlasting guiding principle to good cybersecurity. The core principles remain the same, but the threat landscape is constantly changing and deserves continual monitoring.
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Data will continue to drive business transformations in 2019. Here are three trends that could change the business landscape over the coming year and tips to help you prepare for them. As we prepare for 2019, it's a good time to look back and reflect on the effect that data has had on global business during this past year and what might be in store in the year ahead.
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The digital marketers of the modern day are expected to be competent in a host of skills, which includes sales, digital media, and many more. You need to keep yourself relevant and to close the skills you need a more effective way which is faster if you are investing and committing your life to get a degree in these skills. Having experience can take you more ahead as specialized course training is a must. You need to have good digital marketing skills if a marketer wants to stay competitive. There are several leading digital marketing courses which will motivate and helps you in building a successful career in this field.
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This year's round-up of predictions from industry figures yields wisdom in Data Science, AI, data regulation, data governance, the state of the Hadoop market, open source and "the edge."
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Artificial intelligence is a driving business force in this fast-changing 21st century. AI is no longer an implausible futuristic vision, but a stark reality that is disrupting businesses worldwide. In the 21st century, companies are forced to rethink traditional market approaches and become more service-centric in order to remain relevant.
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Data Science & Cybersecurity, what is big data analytics? Why is machine learning applications so important? Why did InfoSec Professionals require to learn about DS? What to know about "data bots" as a data science professional? Differences in data science vs machine learning? How to crack cybersecurity jobs with data science advantage?
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New digital technologies could bring over $150 billion (Rs10.7 lakh crore) to India's GDP by 2021. So, many Indian professionals are choosing to learn new skills in order to cash in on this economic transformation.
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These days organizations look for the ways where they can prepare the data very quickly and appropriately for solving the challenges of data and enabling machine learning. The data should be cleaned and accurate it should be checked before the data is brought to the model of machine learning or any other project of analytics.
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Data mining is the method of sorting through massive information sets to spot patterns and establish relationships to unravel issues through information analysis.
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Global Software Analytics sales and market share comparison and analysis with an overview of current market status, competition, recent developments, future forecast and major manufacturerâ??s analysis
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The amount of data generated these days from all business domains conjointly called massive data is large, encompassing data gathering, data analysis, and data implementation method.
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Skills of data analytics have become the leading factor in terms of the advanced development and for the career perspective, the demand of the data analyst is increasing day by day. There are several online courses which you would prefer if you want to build your career as a data analyst as it will help you to learn the fundamentals of data science, the key tools of data science and the study of programming languages in the analysis of big data.
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The rates of unemployment are at a lower phase and the economy is booming. There are many companies who are facing the shortage of data engineers and wanted some professionals with high skills. It is really difficult to get skills for both data scientist and data engineer in the same file while taking the step towards it is the personal choice which profiles you want your career to be in.
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Across many industries, there are many large enterprises and businesses having the high performance which are tidily turning towards artificial intelligence and new analytics to make the decisions faster, productively and data-driven.
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Continuous intelligence from all your data is not another phrase to describe real-time, speed or throughput. It's about frictionless cycle time to derive continuous business value from all data. It's a modern machine-driven approach to analytics that allows you to quickly get to all of your data and accelerate the analysis you need, no matter how off the beaten track it is, no matter how many data sources there are or how vast the volumes. It's about not doing this once but letting the machine automate it so it's continuous and frictionless.
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Four forces are deep at work altering the landscape for marketing in 2019 and beyond. The forces and the opportunities they represent are hidden in plain sight. Take privacy for example. Many still view privacy policies as a check-the-box legal exercise, yet consumer attitudes toward privacy and data collection have fundamentally changed.
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Global Video Analytics sales and market share comparison and analysis with an overview of current market status, competition, recent developments, future forecast and Growth analysis
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According to a replacement, eBook OmniSci titled The OmniSci Extreme Analytics Platform: Revamping the expertise of huge data Analytics, all of them use the acute Analytics platform to form a sense of the huge amounts of vital, time period data they're perpetually accumulating.
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Data Analytics tools, latest technologies, and programming languages are required by data science which helps the data scientists to gain meaningful insights and value from the data. A recent survey of nearly 24,000 data professionals by Kaggle revealed that Python, SQL, and R are the most popular programming languages. The most popular programming language was Python 83% used. 3 out of 4 data professionals recommended Data Scientist should learn Python programming language.
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The practice of data science requires the use of analytics tools, technologies, and programming languages to help data professionals extract insights and value from data.
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Modernization and efficiency are essential in the face of the prevailing climate of fierce competition in today's world of business. A huge part of this is being driven by Data Analytics. Due to the market's appetite for high-level skills when it comes to going through a huge pile of data, and analyzing the bigger picture, collecting, managing and providing precise results, this field has become extremely critical.
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Data scientists are increasingly important to organizations as decisions become more data-driven. You need to be able to tell the real and talented data scientists from a charlatan who talks the talk. Here are five questions every data scientist should be able to answer.
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They want to make most of every dollar they spend. Data analysis that helps those small business owners target their customers is an essential element of success, and the quality of that analysis could mean the difference between a profit and a loss.
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They want to make most of every dollar they spend. Data analysis that helps those small business owners target their customers is an essential element of success and the quality of that analysis could mean the difference between a profit and a loss.
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The High Performance Data Analytics Market report highlights the current market size and future potential of the market at the global and regional level with the help of industry trends and market performance.
Source: ReportsandReports6141
So here you can see that machine learning is quite an approaching word in the world. It is the Artificial intelligence tool Machine Learning is the buzzword created and is the next future of the world.
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The large heap of data generated every day is giving rise to the massive information and correct analysis of this data is obtaining the need for each organization. Hadoop is a savior for large Data Analytics and assists the organizations to manage the data effectively.
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Global Health Care Analytics sales and market share comparison and analysis with an overview of current market status, competition, recent developments, future forecast and Growth analysis
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Are you looking for a fresh start in 2019? Maybe you'd like to get fit? Learn a new skill? Or change career? According to analysis from networking site LinkedIn, 2019's employers are looking for a combination of both hard and soft skills, with creativity topping the list of desired attributes. The findings chime with the World Economic Forum's Future of Jobs report, which concluded that "human" skills like originality, initiative, and critical thinking are likely to increase in value as technology and automation advances.
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These days, there are ample of businesses which are started just to know the true potential of gathering and examining the data which is of huge quantity in real time. The cases which are already being discovered the enterprises are becoming proactive with them by leveraging the data of real-time to analyzing the situations of the real-time, predicting the events of future, the process of business is improved by taking the spontaneous actions, regulation is being adhered and the experience of the customer is enhanced.
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Machine Learning is a branch of computer science, a field of Artificial Intelligence. It is a data analysis method that further helps in automating the analytical model building. Alternatively, as the word indicates, it provides the machines (computer systems) with the capability to learn from the data, without external help to make decisions with minimum human interference. With the evolution of new technologies, machine learning has changed a lot over the past few years.
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According to the report of U.S Bureau of Labor Statistics, the rise of Data Science needs will create 11.5M job openings by 2026.
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How you will improve yourself as a Software Engineer? If You are at very first step or starting your career as a software engineer the first step is to get learn your language, frameworks, tools, and technology. But what in the other case if you're an experienced Software Developer, then you should find new opportunities to improve your code for readability, performance, and maintainability and then practice making well-reasoned decisions about where to focus time and resources in your code whether it's testing, performance optimization, or other technical debt.
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Successful DevOps practices generate a huge amount of data, so it is unsurprising that data can be used for such things as streamlining workflows and monitoring in production, and diagnosis the bugs.
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The need for Data Scientists and Data Analytics in India too is increasing enormously with a number of openings left vacant in the past due to lack of the skilled candidates, according to a report.
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The global drone analytics market is anticipated to hit USD 9.47 Billion by 2025 with a CAGR of 30.12% during the forecast period from 2018-2025. In 2017, the rate was USD 1.15 Billion.
Source: https://researchstore.biz/report/global-drone-analytics-market/71560/4566
Over the recent past decades, the numerous sporting events and sports club have seen an effective growth in the amount of revenue created.
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The report implements the SWOT and Investment analysis which helps to predict looming opportunities in Drone Analytics industry. It also assesses new project feasibility to illuminate potent possibilities for novices expected to perform in Drone Analytics market.
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The report includes production data, consumption data and revenue data across worldwide. The Market share and growth rate is also mentioned.
Source: Market Research Explore3174
MRE provides real insight for effective decisions to help business with the help of current industry trends and accurate data available in the market.
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Market Research Explore is a huge market research platform which provides market intelligence reports and consulting services.
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Global Multichannel Analytics Market offers all-embracing knowledge on Latest Industry Trends, Market Status, Geographic Analysis and Financial Outlet.
Source: Market Research Explore2772
The most successful IoT startups in Artificial Intelligence (AI), and real-time monitoring to deliver exceptional customer experiences. Following are the five start-ups for IoT based on their ability to attract the customers and as well as each of these startups is taking a unique approach to solving challenging problems of an enterprise.
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Data is gold and data is all around and the amount of data is increasing rapidly. According to IBM, 2.5 billion gigabytes of data was generated every day.
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Positive returns on analytics investment require management action. But many managers are reluctant to take action based on analytics, especially when the numbers don't seem to match with their own gut understanding.
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A career in data analytics is not only concerned with learning Python or Hadoop, but it also takes into consideration various skills
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A data scientist is the #1 profession in America for 2019, according to Glassdoor. And that is not surprising, given the median base salary paid in the field is $123,000. Still, the data science job market is far from saturated, with an estimated shortage of 190,000 specialists in the US only.
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Now recently Gartner launched its top technology trends for 2K19. The common thread that holds every technology and trends are Artificial Intelligence, Augmented Analytics, Blockchain and many more and all these have the ability to turn data into a business asset. That future growth lies in the ability to turn data into something useful isn't a surprising revelation. But not every organization is equipped to make the most of its valuable information.
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The edge computing was a hot topic as companies began to understand that the edge computing is the new cloud. The transition and adoption will be a big part of IT strategies in 2019 due to a few key trends that will drive that adoption at a rapid rate.
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The fundamentals of robotic process automation combined with machine learning capabilities to robotize the mundane tasks, plus learning to do a job even better, is what intelligent process automation all about.
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I started writing about my experiences taking courses on machine learning and artificial intelligence. One of the big, unexpected problems I ran into was calculus and linear algebra.
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You can't control luck. But the other two, you can. And here is how can (a) find and apply for the right job data science and (b) write the right resume.
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For every business, data science is the foundation of enabling a successful transformation into an AI-powered enterprise. Data analytics and machine learning drive smarter business decisions, greater operational efficiency, and higher levels of customer satisfaction.
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From entering an analytics career to becoming a trainer and mentor in analytics where I am able to inspire people to achieve their dream analytics job and inspire companies to capitalize on their data and insights -- my professional journey is of interest to many of my clients. They wonder how it all happened; what steps and obstacles I met along the way.
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For every business, data science is the foundation of enabling a successful transformation into an AI-powered enterprise.
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Data science is giving too many opportunities today in the professional world. As the number of business concerns using data analytics is on the rise, so is the number of jobs in this field.
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Augmented Analytics and Artificial Intelligence in the spotlight at Gartner Data & Analytics Summit.
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Data science has revolutionized the technological world. We all are aware of the term data science that there is definitely something in data science that sets it apart and make being a data scientist one of the best jobs of the twenty-first century.
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Google's DeepMind artificial intelligence research company is developing a clinical decision support (CDS) tool for identifying eye diseases.
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We are living in an economy which is completely data-driven. Big data courses play a vital role in your career as they can allow you to be a much more effective contributor to the company's bottom line.
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As time flies, now big tycoons are more focused on data. That's the reason many of the people building businesses today are putting analytics and data science at the center of their strategy and operations.
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Everyone knows that the world has changed a lot in recent years. Now, with less than 10 months until 2020, the Cloud is the reality, AI is everywhere, and Voice will undoubtedly be the next interface for analytics.
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Data science teams need content managers. Here are 3 ways you can incorporate content management into your data science and analytics.
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One of the fastest growing careers among them is Data Science, which has become extremely popular among youth because of its exciting nature of work and new newness. Professionals who do this job are known as Data Scientists.
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There are many things which are way too difficult to grab, but sometimes getting way to this uncomplicated language of data visualization sorts everything to a concept which you can get.
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There are several trends in the field where there is a need to be familiar with big data. Big data is the data which consists of volumes greater than 1 petabyte, or 1 million gigabytes.
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When I started working at my latest company all the reporting was done with a combination of Google Sheets and Tableau, with Tableau being the principle reporting mechanism.
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Big data is now becoming popular for the 21st century as it is consumed and utilized by the businesses in large quantity.
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To analyze global Workforce Analytics status, future forecast, growth opportunity, key market and key players.
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Data science and Data analytics are used to identify patterns and draw inferences from raw data.
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Software Developer & Data analysts have been hot properties in Indiaâ??s job market for years. Currently, there are about 97,000 analytics jobs waiting to be filled in India, according to a recent study by ed-tech company Great Learning. This is a jump of almost 45%, compared with a year ago.
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The point of this article is to show you what a successful Data Science job hunt looks like, from beginning to end. Strap-in, friends. I'm about to bring you from day 1 of being laid-off to the day that I accepted an offer. Seriously, it was an intense two months.
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As you can see these days there are millions of data generated and big data has become the most demanding tech in the world.
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It is noteworthy to know the major challenges that a Data scientist face.
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Here are some of the top Data Science companies in India that you must have an eye on regarding their recruitment and selection.
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A Business Intelligence technology is used by the organizations to analyze business information which includes past and present data and drawing insights from that data.
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Social media is just the opposite what it tried to present, as said, leaving everything behind social media didn't come to a period of beating the news behind in any way.
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Augmented Data Science is integrated into the average enterprise, the domain of data science proliferates as does the knowledge and understanding of analytical techniques
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So here is the difference between a website and a web-enabled application.
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More than 97,000 analytics & data science positions remain vacant in India due to the shortage of talent. Here's how to be relevant in the job market.
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A highly professional and skilled having the ability for collecting a large amount of data for analyzing and synthesizing the information into the actionable plans for many companies and organizations.
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So here you can see that machine learning is quite an approaching word in the world.
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The way of predicting the future event in businesses by analyzing the past and current data patterns is called Predictive Analytics.
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Relevant skills, qualifications, and courses will prove good to you in developing a career in Data Science.
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Learning paths are immensely popular among our data science & machine learning readers and with good reason! Learning paths take away the pain and confusion from the learning process.
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Big Data is a popular term you must familiar with it. Big Data is exactly what the name implies as data which consists of volumes greater than 1 petabyte, or 1 million gigabytes. This data is stored in servers and gives different results by using different analysis techniques based on the needs of the users.
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In today's era, so many businesses today relying heavily on data about their customers, products, processes, inputs and the market, these organizations are increasingly in need of talented, skilled people who can extract information and insights from the data.
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There is a tremendous amount of data which is generated by every business on a daily basis. The rise of the internet and the introduction of social media platforms have led to an additional spike in the amount of data generated.
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Companies are investing huge amounts to adapt Artificial Intelligence into their businesses to help them increase their operational efficiency.
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Big Data as defined by Gartner is high volume, high velocity and/or high variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.
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LinkedIn is a very good place for the professionals to gather, connect with others, share ideas and network. If you are in a Data Science or predictive analytics space, or if you are seeking for additional insights and what all industries are talking about, for all these LinkedIn professional groups are a great place to start.
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A data scientist uses statistical methods, such as mix modeling, predictive response modeling, sales response modeling, experimental design, CART/CHAID, latent class segmentation, cross-sectional and time series analysis, discrete choice modeling, data mining and optimization techniques to cater client business requirements.
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It can't be denied that Big Data is a hot topic in present times. But there are businesses still struggling to shift from concept to execution.
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Understanding the types of analytics will what give a beginner a deep understanding of the workings involved with Big Data.
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Data science is one of the most current and diverse fields of technology today. It is all about collecting data which are unstructured and raw in the form and then finding insights from it; can help any venture become more profitable.
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If you need a data center but don't want to deal with a physical one, Google Cloud Platform is the solution.
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This article will dive through some of the most Frequently Asked questions in Data Science Interviews with the help of a popular video of YouTube so that your preparation for the next Data Science interview becomes easier.
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The report by Gartner states Augmented Analytics as an approach that automates insights using machine learning and natural language generation.
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So Internet Of Things continues to grow more and more and it is expected that more than 14 billion devices which are connected will be in use by the year-end and by 2021 it will reach to 25 billion.
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Some common books every beginner should buy and increase their learning abilities.
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Data Science is about using data for creating as much impact as possible for your company.
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Using Predictive Analytics your business could reach to those important points which are important in attaining the maximum revenue out of a limited number of inputs.
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See the major difference between the sub-categories of data science, machine learning, and big data.
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These are some of the top predictions by Gartner on Data and Analytics for 2019 which were published on its recent report.
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How do you study for a field that's changing all the time? Software engineering graduates from three years ago have to start from scratch when it comes to aspects of artificial intelligence, blockchain, machine learning, and robotics.
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There are several updates by Google on firebase, its mobile development platform. Notably, Google is launching new capabilities for ML Kit.
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Data Science books which will benefit beginners, professionals and business people also. You can easily avail these books on Amazon at a Discounted price.
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Through Machine Learning, computers are capable of learning without being explicitly programmed. ML is one of the most exciting technologies that one would have ever come across.
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Either you are traveling to work or are not engaged in any mental activity or have any constraint in your eyes to read a book or watch an informative video you can easily refer to a podcast to get yourself updated in your specialization.
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Many technical skills require training and experience to master. They are also typically a type of hard skill. Hard skills are those that can be taught in a classroom and can be defined, evaluated, and measured.
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Here are some books for learning some famous programming languages like Java, C++, C and many more.
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With the help of Predictive Analytics businesses now predict what ups and down they are going to face in the nearer future. These predictions help a business in taking controlled decisions and thus improves the major business decisions.
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This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python talks about the differences and relationship between AI, Machine Learning and Deep Learning.
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Sisense has acquired Periscope Data for creating a complete data science and analytics platform for customers.
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Here are some machine learning books which will give teach you an in-depth analysis of machine learning algorithms.
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If you think that data science is not a job which needs proper skills, here are some reasons where you will see the fact.
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The Reserve bank of India will promote the use of data analysis to identify cases of fraud and help instant response and recovery actions, such as blocking irregular transactions before payment authorization.
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Here this article will take you with the view of some cities which will entertain you with the highest pay packages as a role of a data scientist.
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Business intelligence includes the strategies or the technologies that any business uses to find relevant insights out of the business data. With the help of Business intelligence businesses takes those important decisions that are required by it to grow.
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Technologies such as Hadoop, MapReduce, Apache Spark have brought a revolution in the ways of analyzing big data. This is probably the best time to make your career in Big Data. I believe, nothing beat books when it comes to learning a concept to its core.
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Learning Cloud Computing is easy when taken the help from the best resources. Books are always the best resources to consider for that. The present article discusses the top level books that every aspirant in cloud computing should refer to.
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Big Data is a buzz today and so Big Data Analytics! According to a piece of information from ResearchandMarkets.com, The big data analytics industry will reach a global market worth of $40.6 billion by 2023.
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According to International Data Corp. (IDC), worldwide revenue for big data and business analytics (BDA) solutions will reach by $260 billion in 2022, with a compound annual growth rate (CAGR) of 11.9 percent.
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Some books which will help data scientist to cope up with professional learning.
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If you want to know that what is Big data, what is Hadoop and how people came to know about Hadoop, this Hadoop tutorial will teach you the exact meaning of it.
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When we see that deep learning models are being trained, NVIDIA might bet full attention. However, Intel is not sitting quietly, just staring at the massive AI opportunity.
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As companies need to deal with the Big Data every day, recruiters look for the skill of handling this Big Data in the potential candidates and questions on Big Data and Hadoop are the most frequent one asked by recruiters in the interviews.
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Using Big Data Analytics a number of patients' lives have been saved because it has become possible for health practitioners now to predict the chronic diseases of the patients with the help of smart predictive software.
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Often we commit the silly mistakes in Data Visualization which lead to wrong interpretation of the data, but with good practices and good techniques effective visualizations could be created in a lesser amount of time.
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Business Analytics helps businesses to understand what has happened in the past along with the predictions of what will happen in the future. Business analytics makes these predictions with the help of historical and present data of Business.
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To make any business successful and work for a longer time, a Proactive and forward-looking approach is needed and this is the only approach by which businesses plan strategies for the future. Using Predictive Analytics businesses make use of their past and present data to predict future certainties.
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You may have learned about the top skills of Data Scientists through various blogs, but learning from an expert is the one thing that you should do now.
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You may have learned about the top skills of Data Scientists through various blogs, but learning from an expert is the one thing that you should do now.
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Handling Big Data is the major priority of businesses today. In this article, we will go through 5 such amazing books to handle big data.
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For acquiring the data analytics platform looker in a $2.6 billion, Google has announced plans for all cash transactions.
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Rather than wait for want ads to go unfilled, organizations should rethink, retrain, reorganize and reach out to fill the data science talent gap.
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Cisco will be introducing new AI and ML capabilities to allow IT Teams to function at machine speed and scale through personalized network insights.
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A data scientist is integral to an AI or ML process, in the sense that all of these projects are depending on big data or complex inputs. The data scientist is the essential careerist who knows how to work with data to produce results.
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A world where 2.5 quintillion bytes of data is produced every day a professional who can take all these enormous resources and provide the frameworks for a business solution is indeed a hero. In this module, we are going to talk about how to become a big data engineer before we begin we talk about the role and description.
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To attract data science talent, you need a sound data strategy and an established data-driven environment in which data scientists can have an impact and do meaningful work.
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Here is the video of Chatbots using TensorFlow which will give you an idea about what are chatbots and how did they come into existence. It provides a brief introduction about all the layers involved in creating a chatbot using TensorFlow and Machine Learning.
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House of bots offers tech-related information, like Artificial technologies, Machine learning, Robotics, Chatbots, Data analytics, Neural Network, and Cloud computing. HOB is the solution for different users like tech-savvy, job providers and job seekers, etc. HOB is a B2B platform.
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To ensure effective implementation, one of the first things to prioritize is choosing the right data analytics software. A good place to start is getting to know the leading products in the niche by checking out the best data analytics software.
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It is the toughest job to find Developers with skills in Java and Python programming languages as the UK's skills shortage spreads beyond the capital.
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Machine Learning is a branch of computer science, a field of Artificial Intelligence. It is a data analysis method that further helps in automating the analytical model building.
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A data scientist will be responsible for designing and implementing various processes and different layouts for the intricate and large-scale datasets that are basically used for modeling, data mining, and various research purposes.
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Take free online business intelligence courses to build your skills and advance your career. Learn business intelligence and other in-demand subjects with courses from top universities and institutions around the world.
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Going forward, big data analytics will continue to tell companies what the users want. This will have a significant impact on how funds are distributed across genres.
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Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Here are some famous machine learning tools to learn from some famous books.
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Since the importance of data analytics is burgeoning day by day, hence the companies are appointing the sagacious professionals who will provide the company with the wider insights of the structured data.
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The information technology sector has some of the most lucrative jobs in the world. According to data from jobs site Indeed, the IT space has been the most consistent in jobs growth over the past five years. Between February 2018-19, there was a 31-percent rise in technology jobs.
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Hadoop and Big Data Analytics industry report covers the prospects of Hadoop and Big Data Analytics in the forecast period of 2018-2026 and the scenario.
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Microsoft India today launched the Digital Governance Tech Tour to help accelerate Digital India. The program aims to deliver critical AI and intelligent cloud computing skills to the Government officials in charge of IT across the country.
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Microsoft India today launched the Digital Governance Tech Tour to help accelerate Digital India. The program aims to deliver critical AI and intelligent cloud computing skills to the Government officials in charge of IT across the country.
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The Econet Global Group has announced from Accra Ghana their partnership with American startup, Atlas AI.
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Jobs requiring machine learning skills are paying an average of $114,000. Advertised data scientist jobs pay an average of $105,000 and advertised data engineering jobs pay an average of $117,000.
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Investments in the Internet of Things will increase in 2019, even as the term 'IoT' begins to fade. Here are the five most significant trends that organizations can expect, according to Forrester Research.
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Big data analytics is all about how you store the huge amount of data and how you process it to get meaning out of it to draw conclusions and make the correct business decisions.
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The overall importance of data and information within organizations has continued to grow. We've also seen the continued rise of megatrends like IoT, big data - even too much data - and of course, machine learning.
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Ernst & Young (EY) a multinational professional services organization and one of the Big Four accounting firms are set to hire 14,000 new employees for their global delivery center in India. EY currently employs 27, 000 people.
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The emergence of relationship analytics highlights the growing use of a graph, location, and social analytical techniques.
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Big data isn't quite the term de rigueur that it was a few years ago, but that doesn't mean it went anywhere. If anything, big data has just been getting bigger.
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Machine Learning is the buzzword created and is the next future of the world. It is defined as an artificial intelligence tool that works as an artificial mind to learn automatically without the presence of the human mind.
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Big Data operates irrespective of any field or size of the business, as management and collection are done in every field; thus, making it more accessible.
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The Internet of things (IoT) has driven every object in the globe into the digital realm.
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Big Data Hadoop is one of the most progressing technological fields in the present day. Just like the changes in the trends of the world, many changes have also been made in the different fields of technologies.
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An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
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Data is a word that is pretty known to us. If we put it into correct words, it is a collection of information that can be translated into a form that can be processed by computers.
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Today the saying 'knowledge is power' fits perfectly for the internet. Tons of data is transferred over wireless connections in the world, but its management can be hectic for an unprofessional.
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Here are a few programming languages we recommend for coders who want to make it big in 2020.
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Data science strategy for Dummies begins by explaining what exactly data science is and why it's important.
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The sets of raw facts and figures which are so complex and bulky that they cannot be dealt with using ordinary data processing software are called big data.
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Data Analytics refers to the process of collecting, organizing, interpreting and extracting useful insights from the raw facts and figures in the huge amounts of data generated by a business on a daily basis.
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Data analytics is no longer an unknown term. Data analytics is simply collecting, organizing, analyzing and gaining useful insights from raw data.
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Learn how big data is driving organizational change and essential analytical tools and techniques, including data mining and PageRank algorithms.
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The Big data revolution and cloud computing are in a convergence state and companies are changing the way they think in terms of doing business to incorporate data that will drive their decision-making process.
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Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell
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Data Science is a combination of the following skills: Mathematics expertise, business/strategy acumen, and technology and hacking skills.
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Below is the list of top 10 of data analytics tools, both open-source and paid version, based on their popularity, learning and performance.
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Big data analytics deals with data primarily and the predictions or forecasts from analyzing databases that help with informed decision making in all processes related to business.
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Artificial Intelligence, the name is getting rich & popular in the tech world and making the world groove along with technological shifts.
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Data Science refers to studying hidden insights behind the data and manipulating them in order to find logical solutions to problems in business and industrial contexts.
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As the analytics industry has grown over the years, it has given opportunities to companies to create tools that specifically cater to specific aspects of the data analytics procedures like data transformation, data formatting, visualization, etc.
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The confusion often arises from the fact that there is an overlap with regard to programming skills. Listed below are some of the key differences between Software development and Data Analytics:
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If you're wondering how artificial intelligence might affect your business in the short term, and even over the long haul, this article will help you keep your finger on the pulse.
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Big Data Infrastructure Management in Cloud Data Centers has been one of the fruitful solutions suggested for countering rising infrastructural costs.
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As the analytics industry has grown over the years, it has given opportunities to companies to create tools that specifically cater to specific aspects of the data analytics procedures like data transformation, data formatting, visualization, etc.
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Over the past many years, the Artificial Intelligence revolution has provided a quality response to the different range of technologies.
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Data analytics has become indispensable in many industries. It is firmly embedded in the way a lot of companies to do business.
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Deep Learning has been an important Artificial Intelligence technique that allows the computers to establish how to recognize the desired sentences, objects or words.
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DevOps is the evolution of traditional application development and operations roles driven by the consumerization of all software and business demand for agility.
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Artificial Intelligence (AI) has the potential to completely redesign the way in which businesses operate across functions, including customer service, marketing, and finance.
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Big Data is a term to become familiar with if you watch the trends in the IT field. Big Data is exactly what the name implies: data which consists of volumes greater than 1 petabyte, or 1 million gigabytes.
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Along the way, you'll get an introduction to working with data and some fundamental concepts and technologies for Big Data scenarios.
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Today's business marketplace is driven by tons of data. In fact, data is an important aspect of all industries as date offers plenty of useful information that helps businesses make important decisions.
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Many companies, both large and small, are attempting to find ways to leverage value from their silos of unstructured data, through applied analytics techniques such as Natural Language Processing (NLP) and sentiment analysis.
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Today data science is being used by industries, so prolifically that the demand of data scientists has risen too.
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Big Data and analytics are primarily reforming all aspects of the travel industry, and companies that do not adapt will be lagging behind in the data-led industry.
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Artificial Intelligence, or simply termed as AI, as the name suggests, is the intelligence exhibited by the machines.
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