Nowadays, nearly every other business is thriving with the help of data. This has been possible with the enormous amount of growth in big data domain. Big data is helping organizations make faster decisions than yield higher ROI and improve their customer experience. These factors have generated a tremendous demand for big data professionals. Furthermore, many students are considering pursuing a career in big data by undertaking PGDM in Business Analytics.

If you are interested in pursuing a career in the flourishing industry of big data, then you would be interested in understanding more about that career options that you can pursue after completing your PGDM in Business Analytics. So, to clear your confusion, in this article, we have made a list of top career profiles that would be right for you.

Data Architect

A Data Architect’s role is to manage the complete data infrastructure of a company. It is their primary responsibility to create and manage the overall data architecture. Furthermore, it is their task to define how the organization would be storing, analyzing, and managing data. The other responsibility of a Data Architect is to ensure that data storing procedures adhere to government regulations.

Business Analyst

A Business Analyst’s primary role is to understand the requirements of all business stakeholders. After determining requirements, they with their data analytics skills, develop cost-estimate modulus and deliver data-driven recommendations. Some other duties of a Business Analyst include improving processes by streamlining current practices, understanding customer needs, among other things. In short, a Business Analyst primarily acts as a bridge between data and business.

Data Scientist

Data Scientist is one of the most critical positions in the big data industry. The reason behind this is, Data Scientist is the one who knows how to extract meaningful data from a vast array of unstructured data. To do this, they have to invest most of their time in collecting, cleaning, analyzing, and processing data. Along with it, they identify trends and patterns to help businesses increase profits. To perform all of these tasks, a Data Scientist needs to use various tools, methods, and machine learning.