Business Analyst vs. Data Scientist

Data Science, AI and ML
#1

Business Analyst vs. Data Scientist – A Simple Analogy

Let us take an example of an exciting electrical vehicle startup. This startup is now big for creating job families. And, they have decided to create three job families, one is a scientist , and the other two are an engineer and a management professional. Now I want you to take time and imagine what kind of role they play in the company.

We can infer their role from the general level of understanding:

  1. Scientist – Work on complex, distinct problems such as finding a solution to build an efficient battery, or how to improve the design of the vehicle. While these problems may not give direct gain to the company but are crucial for advanced developments. And, in the future, these developments can help startups have non-linear (exponential) growth.
  2. Engineer – Take these developments and apply industry techniques to transform them into production. For example, making an assembly line to manufacture these vehicles using the right machinery.
  3. Management – Run the business and solve business-related problems on a day-to-day basis. For example, to find the right market to open a store for the vehicle. Decisions regarding the sales and marketing of these products and many others.

Now, let’s take these roles and convert it to data-based profiles.

Data-Based Functions:

Business Analytics Vs Data Science

  1. Data Scientist – He Works on complex and specific problems to bring non-linear growth to the company. For example, making a credit risk solution for the banking industry or use images of vehicles & assess the damage for an insurance company automatically.
  2. Data Engineer – He would Implement the outcomes derived by the data scientist in production by using industry best practices. For example, Deploying the machine learning model built for credit risk modeling on banking software.
  3. Business Analyst – Run the business and take decisions on a day-to-day basis. He’ll be communicating with the IT side and the business side simultaneously.

This is a very basic analogy that you need to keep in mind to differentiate the role of Data Scientist, Business Analyst, and Data Engineer.