Data Scientist, what’s that?


So with the advent of BIG Data and almost every business now trying to use it to grow their business, improve their top lines or just improve efficiencies, there is a HUGE demand building up for people who really understand how to use the BIG Data.

For the uninitiated BIG data is a nothing but large volumes of data – both structured and unstructured – that gets captured by businesses on a day-to-day basis. However it’s not the volume of data that's useful necessarily but the insights that can be derived from analysis which can lead to better decisions and strategic business moves. Key features or characteristics of BIG data are Volume, Velocity, Variety and Veracity also known as the 4 V’s of BIG data.

However today we are not discussing the BIG data but the people who know what to do with the data. These are guys are commonly known as Data Scientists. Data scientists are big data wranglers, gathering and analyzing large sets of structured and unstructured data. A data scientist’s role combines computer science, statistics, and mathematics. They analyse, process, and model data then interpret the results to create actionable plans for companies and other organizations (source: 2U, INC.)

To simply put, the data scientist will take all types of data i.e. structured or unstructured, design models that will eventually make sense of all the data. So let’s take an example of Netflix, and a data scientist trying to work on their data. Now the type of data that it will generate would really be around the content the users are consuming online on the platform. However a data scientist would be able to make multiple analysis and create insights around

  1. The genre of content most watched, i.e. Horror, Romantic, Action – This can help Netflix decide which type of content they should produce or purchase.
  2. The demographics i.e. sex ratio, age of users, location etc. – This will help in targeting marketing of content, younger crowds would be more interested in high school drama and reality series, older generation interested in documentaries etc.
  3. The times when the content is most downloaded – This will help Netflix making sure their servers are at full capacity at these times so that the users do not face any lag or system challenges.

And like the above insights, the data scientist can provide extremely helpful information which can help grow business and manoeuvre in the right direction. The data scientists therefore are used by almost all the top companies to help make better decisions and reduce risks.

Some of the skills required to become data scientist are Programming, Machine Learning techniques, Data Visualization and Reporting, Risk Analysis, Statistical analysis and Math, Effective Communication, Software Engineering Skills, Data Mining, Cleaning and Munging, Research, Big Data Platforms, Cloud Tools and Data warehousing and structure. There are enough colleges and universities that provide diploma and degree level courses to become a data specialist.

Therefore if you have it in you and love the idea of data crunching, analysing and investigating the relationships between all sorts of data then this field is definitely worth pursuing. 

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