What is the Difference between a Data Scientist and a Business Analyst? Which would be a Better Career Choice for Me?

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I often get this question often from people making inquiries. I’ll try to answer in the simplest style possible.

The Data Scientist and the Business Analyst are two friends who would usually catch up in official meetings. The reason is because their roles are mutually complementary. The Business Analyst knows what to do - he knows the specific pain areas of the business and the opportunities the business is trying to take advantage of. He knows the requirements from the various categories. The Data Scientist knows the latest solutions to the problems.

If kept separate, the Business Analyst would interact with the client or the marketing team, get a top level grasp on the required data, present the needed statistics and suggest lucrative solutions to the organisation/tech teams. The BA can be a standalone player or part of a team of BAs where they all work to distill data and understand the processes using more or less traditional means.

Meanwhile, a young Data Scientist working by himself would just jump into implementing and plugging in all the latest tools and techniques he’s read about in research papers and blog posts - not because they are the best solution, but because that’s his job - that’s what he knows how to do.

The Business Analyst knows the best WHAT, the Data Scientist knows the best HOW.

When the Data Scientist (DS) and the Business Analyst (BA) work together, the DS prepares the “big data” processing infrastructure while the BA is engaged in discussions with clients or senior managers who are responsible for defining the requirements and expectations. The BA then plans for the implementation details with the DS. The DS trains his “models” and processes the data with it. He creates packages that can be used by the other teams. He creates visualizations that provides insights into the data and the interrelationship between ideas, concepts and data. The job of the DS might involve a lot more depending on the exact job profile.

What are the skill set required for performance in these areas? If you love mathematics, programming and tinkering with new software tools (programmable), Data Science might be the way to go for you.

For greater degrees of clarity, here are some of the skills you should learn to be a competent Data Scientist:

  • Programming in multiple languages with a good hand in at least one of them

  • Data Structures and Algorithms. This is what you need to be really good in any fields related to the Computer Sciences.

  • Solid mathematical skills. You shouldn’t be afraid when someone talks about Matrix Factorization or Gaussian Distribution. Elementary Calculus is also required - basic knowledge is sufficient.

  • Tinkering with numerous things. You might have to work with massive clusters of system, play around in the command line and so forth.

  • Machine Learning and Pattern Recognition. Not as easy as blog posts might make them seem, but not too difficult either.

  • And Persistence, Perseverance and Patience.

The skill set required for success as a Business Analyst would correspond to the 6 Underlying Competencies very well defined in the BABOK.

  • Analytic Thinking and Problem Solving

  • Behaviourial Characteristics

  • Business Knowledge

  • Communication Skills

  • Interaction Skills

  • Tools and Technology

Most of these, we would discuss in subsequent posts. 

I hope you found this helpful?