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Being a Data Scientist

By Pradeepta Mishra, Chief Data Scientist, AI Architect - Ma Foi Analytics | Thursday, 12 Oct 2017, 11:10 IST

As data science is emerging as an upcoming domain altogether there are various reasons for this growing field and the main cause being the increased digital penetration. Almost all the businesses are going digital, making their awareness felt digitally. When digital communication happens, it generates activity, log, transactions, trace and a long history of data. When businesses build their huge data bases and warehouses to hold the massive amounts of interactions and history, they also want someone to look at the data, find out the pattern and someone for informed decision-making.

Second; emergence of various programming languages, especially open source languages, makes the statistical learning and model creation much flexible than before. Hence, many professionals having statistical and mathematical background find data science interesting to apply their knowledge, using open source tools. Third is the tremendous opportunity to take the professional career to the next level by working on the skills. The emergence of artificial intelligence and machine learning for process automation also plays a role of significance. Many professionals want to work on their skills just to stay relevant in the current changing market dynamics. 

Nevertheless, there are numerous pros and cons of taking up data science. The pros of becoming a data scientist is to know everything and be a master in each of the three circles and the cons of becoming a data scientist is if the person does not know something from the other circle. One example: a person may be a good statistician or mathematician but if the person lacks good programming mind set and lacks domain knowledge, then it is one of the disadvantages of becoming a data scientist. Knowing everything is a challenge for a data scientist as the information is growing day by day and so are the tools.

Organizations' overall success depends on the right strategy it is making, for building right strategy information and insight is required at right moment and right place. For creation of insight, the role of a data scientist is very critical. The data scientist is the one who will fetch the data, mine the information and if necessary create/apply predictive models to know events a priority to help the business stake holders to take informed decisions. 

Today, professionals from various backgrounds are aspiring to become data scientists .However, it was not the case till the last couple of years, but from last year various educational institutes offering post graduate diploma in business analytics, data science and big data, amongst them INSOFE, Great Learning, UpGrad and so are the leading ones. Some of the premier institutes also started training on data science and machine learning.

I would recommend the young generation to pick up an area and do specialize in that area for example, image recognition, speech recognition, sensor identification and so on. To be a successful data scientist pick up problems, not data, if you torture data for some hours it will confess to something, but there is no guarantee that it would be meaningful. Hence, try to solve problems with data and with machine learning and programming. (As told to Riya Das)

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December Special 2017
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