Jyoti Nigania

Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree. ...

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Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree.

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Mapping Use Cases of Data Science Across Different Industries

By Jyoti Nigania |Email | Apr 9, 2019 | 1356 Views

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. There is data everywhere, from all kind sources, whether internal or external. All this data tells a story and depicts something useful which a business should understand to create more productive strategies.

Data Science:
It is a pipeline of activities all structured together. It starts with collecting the data and then storing them in frameworks. Then it is followed by cleaning the data to remove the unwanted and duplicate parts of the data and also correct the erroneous bits and complete the incomplete data. After all the pruning is done, it is followed by analyzing the data using many statistical and mathematical models. This phase is to understand the hidden patterns in the data. All of this is then finally followed by communicating everything to the top management so that they can take decisions regarding new products or existing products.

These days, one can find several data science courses to become a trained professional in the field of data science, and why not? The jobs will soar up to 28% - 30% by 2020, which means more opportunities. To be a data scientist, one necessarily needs not to have too much experience, even fresher with mathematics, computer, and economics background can get trained to be a data scientist. This soaring need for data scientists is because of the rising application of big data in almost every industry possible.

Data Science In Banking And Finance:
Today, many banks are using big data to analyze customer's financial behavior and give relevant banking advice to them. This increases the ease of banking among customers and also they get personalized banking to advise and information. Big data is also helping banks to fight fraud and identify nonperforming assets.

Data Science In Construction:
This is an industry which needs to track a lot of types of data regarding customer value, materials and land costing, revenue, future prospects of land, etc. All this has become super easy as big data helps in analyzing the data and give insights about the decisions to be taken.

Data Science In Retail:
Retail businesses rely entirely on inventory and customer happiness as two major pillars of their core business. Both these facets can be taken care of by big data and its analytics. It can help in understanding the recent trends and customer demands, also to analyze customer feedbacks and most importantly handle inventory and warehousing.

Data Science In Transportation:
Transportation industry uses big data to analyze the routes and journeys. It helps in mapping the routes and provide people with the shortest journeys. It also helps in tracking traveling details in the past and provides customers with customized travel packages. Big data also help the rail industry by using sensor-generated data to understand breaking mechanisms and mileage.

Data Science In Medicine:
It helps in managing and analyzing medical and healthcare data which in turn helps in decision making by doctors. Also, it helps in safety inspections, makes hospital management more effective, tracks patients vital signs and also helps in disease diagnosis. It is ubiquitous and will grow exponentially even in the upcoming years, thus making data science a promising career choice.

Source: HOB