Business Analytics Vs Data Analytics ( Data Science)



Although there are many articles on it but as a career or job role point of view I need some clarification. Rather than asking a very specific question I think asking this would be more relevant.

After doing my Engineering I worked in IT (technical) and then did MBA where i got exposed to business analytics. I have decent knowledge of descriptive / inferential statistics, did few minor projects in PCA, Association rule mining, Regression, Optimization and Simulation created reports all related to business scenarios. I used tools like SPSS Stats, SPSS Modeler. I also completed the Data Science track of John Hopkins University. Currently in a job role very less exposed to analytics but i want to move to it for

So the question is - How business analytics is different from Data analytics ? All answers and suggestions are welcome, I am trying to move to analytics career so anything in perspective will be helpful


Hi @AnanyaPandey.

I like to think of data analytics as a profile which needs to have some sort of technical background especially in domains like data retrieval, visualization, etc. The Whole work will be based on deriving insights and trends from the data. A blend of managerial and technical is needed to be a good Data Analyst.

For Business analyst, its focused only on the optimization part of business. It might involve using data for making better decisions or might not. But generally, technical skills isn’t one of the top skills required for this role. Skills like structured thinking, problem solving, etc are more important here.

I do acknowledge the fact that terms like Business analyst, Data Analyst, Data scientist, Data engineers can be a bit confusing at times to differentiate. I’ll like to suggest you another resource which might help you understand the differences between these two roles.


Hi @AnanyaPandey,

My view - In any organization there are two very important workflows (or pipelines), the Data Science pipeline and Business Decision making pipeline.

  1. Data Science Pipeline - This is about converting data into insights (predictions, patterns, etc.) on specific business parameters / drivers. This pipeline includes data management, data engineering, modeling etc.

  2. Business Decision making Pipeline - This is about utilizing different business parameters / drivers to create models (like Financial Models, Media Mix models in case of marketing optimization, Supply chain process models etc.) that help us to take a business decision (Ex:Setting a product price, Run a particular campaign, Invest in a particular distribution channel etc.)

Data Analyst is more proficient in data science pipeline while business analyst is more focused on the second workflow mentioned above. So the business analyst tends to have a good understanding of business context, domain knowledge, functional orientation etc. Having said that, the real opportunity is to combine the two pipelines seamlessly so that the insights on business parameters are automatically fed into model equations that helps to take a business decision.

Hope this is helpful. Thanks.

which ones better for career , MSc Data Analytics at Strathclyde business school or MSc Business Analytics from Alliance Manchester Business School?

Thanks for writing, It does help me differentiate both. The whole idea about asking this question is to find out how should I proceed with my career to move into this direction. First question for me is to know how much more of technical knowledge do i need for this profile. Or What should I do next !? Asking this would be too specific but if at all in general you can answer it would give me some direction to move on. Thanks.