Data science can be used for almost anything and everything in today's world, and why not? Every industry is producing and collecting a huge amount of data every day using faster computers. Though data analytics is not a new idea using sophisticated tools and using it as a regular business process is a new thing.
Domestically last year's analytics industry earned $1.27 billion, and this number proves how data science is growing at an exponential rate. Thanks to several programmed and successful tools, day to day activities of a data scientist have become easier and a lot more efficient. And this is the reason why every sector is using analytics for appreciating their business value.
APPLICATIONS OF DATA SCIENCE
Using analytics at the right time for decision making and analytical problem solving can optimize the performance of the business by building brand value, communicating with customers and clients, increasing customer retention and satisfaction, identifying market opportunities for new products and checking the performance of an innovation.
All these benefits are earned by business units through various applications. Some of them are:
Healthcare: This sector is using analytics for the betterment of many medical branches. Medical imaging uses machine learning, content-based medical indexing, wavelet analysis, etc. for accuracy and efficiency in texture imaging. Also, genetics research uses it for advanced personalized medical treatments. Currently, virtual medical support is the new domain of medicine where data science is used profoundly.
Internet search engines: Google, Ask, Bing, etc use data science to optimize their efficiency. When anybody searches anything, search engines use algorithms to find the best suitable results in a second from huge amounts of data and present it to the user.
Web site recommendations: This is used by many digital platforms like Amazon, Netflix, Google Play, YouTube, etc. for providing better customer experience. It uses past searches and activities to use as requisites and gives suggestions to the users.
Image and speech recognition: End-users use these technologies for a better virtual experience. Image recognition can identify images, photographs, and screenshots and give insights on them. Also, social media platforms use image recognition for tagging and searching for people. Speech recognition is used by Siri, Bixby, Cortana, etc. to understand and process the vocal orders by their users.
Airline route planning: Data science has helped airlines in improving their occupancy ratios and operating profits. Analytics help airline businesses in predicting flight delays, planning route schedules between destinations, buying aircraft and running customer loyalty programs.
Fraud detection: Financial institutions are using analytics to detect and mitigate the frauds and risks of the market. It is helpful in identifying bad loans, risky investments, and time to trade and sell. Analytics use customer credit patterns, expenditure history, market sentiment, etc.
Targeted advertising: In the world of digital marketing, digital advertising is experiencing a lot more success than traditional advertising techniques. Digital billboards to digital banners on websites everything is controlled and executed according to data science insights. This targets the audiences who are suitable and show the potential of being future customers.
The demand for data scientists is on the rising after heightened use of analytics in every sphere of commerce, and that is why a data scientist on average takes $124,000 home every year.