4 Things Every Business Analyst Should Know About the World of Data

You must have heard of Big Data, Data Science, Business Intelligence, Data Driven. Maybe not. What do all these cool words mean for a Business Analyst?

Is there any difference between IT Business Analyst and the Data Scientist?

Let’s define each of these concepts

Now that we have defined these concepts, let’s look at the relationships between each concept. Below explains how each concept relates to each other.

The diagram below illustrates the relations between the concepts further:

Data Science is intended to create and define the Business Goal and is presented in the most popular CRISP-DM approach (Ref4- Shearer C., The CRISP-DM model shown below).

A key part of Strategic Enterprise analysis as outlined in the BABOK (Chapter 6, Page 99) is the creation of a business goal or vision. Business goals and visions are elaborated and defined clearly based on many factors including a data driven approach. Having clear business goals and visions creates a more solid foundation in which programs and projects can be based. Does your project charter contain the data driven results to support the need for the project? Building a strong depends on many things, but a key part of that business case is the data to support the investment.

The first two steps in CRISP-DM requires the good understanding of both Business Process and Data Needs, which is similar to Phase-B and C of the TOGAF circle. Which role can be competent enough for taking care of the first two steps and bridging them seamlessly? I would argue that the Business Analyst is a good candidate for this role as they have the specific skill sets to perform the work of creating specific business goals and visions. In today’s world, the BA typically works just at the project level and rarely gets the opportunity to formulate the business vision and goals. A Business Analyst can then take the vision and goals by using data science to build data sets that support an organization’s vision and goals.

Mckinsey’s report “The age of analytics: competing in a data-driven world” mentions the following “Many organizations focus on the need for data scientists, assuming their presence alone will enable an analytics transformation. But another equally vital role is that of the business translator who serves as the link between analytical talent and practical applications to business questions. In addition to being data-savvy, business’s translators need to have deep organizational knowledge and industry or functional expertise.