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How to Kick-start Your Career In Big Data & Data Science

Big data has become the new buzz word in this decade. If you’re looking for a big leap to transform your career, then you should explore this extremely abundant field of big data. Data science is the new frontier of the 21st century right now. The data analyst jobs are extremely attractive, lucrative & fulfilling. A lot of major organizations have realized the dynamic future of analytics & have started to create teams in order to prepare themselves for the big data revolution. But there’s a huge inadequacy of skilled people in big data who can help the organizations to make the most of the data. Before entering into data analyst job, here are the top tips to prepare:

  • Learn the essential tools. Pick up any tool that you can get access. This will help you in mastering one tool & few techniques of the tool, so that you can showcase yourself perfectly for the data analyst job. Educate yourself properly. Understand the landscape of analytics & recognize your ideal data analyst job.
  • To step into the world of big data, you must read plenty on analytics. Consider joining blogs on analytics & keep abreast of the current happenings in big data. This will help you to keep track on how analytics is incorporated in different industry & bolster your knowledge.
  • After learning enough about big data, join the analytics community & discuss about different topics on a regular basis to become more aware.

Career Path

  • Business Analyst- This role needs frequent interactions with databases, both relational & non-relational, including the big data frameworks as well. The data analyst is concerned with pulling from the data, managing it & designing the infrastructure to manage the data. The role of the data analyst requires skills based on SQL, relational databases, NoSQL databases, data warehousing & mastery of relevant tools.
  • Expert Programmer- This role requires deep knowledge in conducting numerical & statistical analysis with huge data sets. You should know languages such as Python, R, Java & C++. Another important aspect of programming includes frequent interactions with databases through queries. You should get comfortable with tools such as R, HIVE, SQL, Scala, HIVE.
  • Data Management Professional- This is one of the important roles in big data. The big data professional is involved with managing data & infrastructure which supports it. The key skills needed for the role are: Apache Hadoop, Apache Spark, NoSQL databases & SQL.
  • Solutions Expert- The Solution Expert is involved with understanding the problem to be solved & has the relevant prowess in building the appropriate analytical framework to achieve the solution of the problem. They are also called as Analytics Architects.
  • Machine learning researcher- They are practitioners known for creating & using the predictive tools to leverage data. This allows the application of statistical analysis at high speeds. The key skills required for this role are: deep knowledge of statistics, algebra & calculus, programming & understanding of machine learning algorithms.

The increasing demand for big data shows there’s ample of opportunities for any big data professional right now. With such demand, there’s no doubt that the market for analysts will be slowing down anytime soon.

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Comment by nikhil sonap on July 10, 2017 at 10:12pm

Great piece of knowledge. With increasing demands even i opted for Big data certification and the results were worth the effort, especially Data Science Council of America helped me in achieving the desired landmark. 

Comment by Wiki Adams on July 6, 2017 at 2:36am

Wow... nice blog.This blog cleared my doubt regarding the careers in data science.

Comment by Pency Parkinson on July 5, 2017 at 9:11pm

Nice article. I did not know that. Nonetheless at last I realize more or less everything at this point. Awesome blog.

Comment by Barkha Sharma on June 22, 2017 at 10:12pm

Hey! Very precisely and well-written article. Found it very helpful. Thank you for sharing.


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