Business Intelligence and Data Analytics Careers That Are Shaping The Future

In their October 2012 issue, Harvard Business Review named ‘Data Scientist’ as the sexiest job of the 21st century. The prognostication turned out to be more than true as 2019 saw 2.9 million data science job openings globally.

For most businesses, data is a goldmine of information around which they can set up their business operations. Businesses hire data scientists to gather, mine, and analyze data which helps them make data-driven decisions, which are more effective and informed.

It is no wonder then, that across various industries, jobs related to business intelligence and data analytics (BI/DA) are seeing a huge surge. In this blog, we will be taking a look at the most in-demand BI/DA careers that will shape our future.


A data scientist’s primary responsibility is to make sense of data. Data Scientists gather, analyze, and interpret large volumes of data to improve an organization’s decision-making process and make their operations more efficient and effective.

A Data Scientist’s job can be approached from two angles – technical and analytical. The technical side of the job involves database management, processing data using data visualization tools, and using machine learning tools to create predictions. This job profile requires an in-depth knowledge of technologies such as Python, Apache Spark, SQL, Hadoop, etc.

On the analytical side, Data Scientists gather, analyze, and interpret data to discover trends and patterns that may help business organizations. While Data Scientists with an analytical bend also tend to be adept at coding technologies, their work also involves proficiency in statistics and mathematical models.


Those interested in a career as a business analyst are required to display high BI/DA skills coupled with exceptional business management and leadership skills. Business Analysts conduct research and analysis of data to help businesses improve their business processes. In a way, business analysts bridge the gap between technology and business using data-driven decision-making.

To become a successful Business Analyst, business soft-skills such as creativity, critical thinking, communication, and leadership are very critical. Business Analysts play a crucial role in helping their organizations move towards more efficient business processes and maximize efficiency. Check out our MBA Program in Business Intelligence and Data Analytics to understand how business management skills can help you lead business analysis.


The job profile of a Data Architect is a highly technical role that involves the use of advanced programming and database management tools. A Data Architect’s job is to design robust data frameworks for large databases for businesses.

A Data Architect designs the database architecture as per the end-user’s requirement or expectation. A Data Architect also monitors and addresses any technical problems in the database frameworks. Hence, Data Architects must have a keen eye for detail, strong analytical skills, and dynamic database management skills.

A Data Architect’s role is extremely crucial as data has to be relevant, accurate, and accessible by the end-user for whom the database has been designed and set-up.


Machine learning is one of the most in-demand careers in the data science industry. With the demand for Artificial Intelligence and Machine Learning (AI/ML) skills rising across the spectrum, many universities and colleges have also launched specialized AI/ML courses. Check out our M. Tech Program in Artificial Intelligence and Machine Learning. Machine learning is still largely in its infancy, but large organizations around the world are already banking on machine learning to create predictive models to make proactive business decisions. A machine learning engineer’s role involves collaborating with data scientists and data architects to deliver data-driven algorithms that will improve business efficiency and user experience.

A machine learning developer’s job requires very high competency in programming such as Python, Java, and C++, data frameworks such as Hadoop or Spark, ML frameworks and libraries such as TensorFlow, Keras, Matplotlib, etc.


As already discussed before, data is king in the present world. Data-driven systems and business decisions are virtually running the world today. In recent years, another buzzword has come to the fore – Big Data. Big Data refers to large sets of data sets that a business collects daily. The reason this data is referred to as Big Data is that this data is ever-growing and traditional data management tools come up short while processing this volume of data.

A Big Data Analyst’s responsibility is to gather, organize, and analyze this data. Big Data Analysts must have excellent technical skills as they are responsible for evaluating a very large volume of data sets, create best practices for database management, and execute big data processes such as parsing, filtering, and enrichment.

A Big Data Analyst’s job profile involves excellent technical abilities, knowledge of database management tools, a command over cloud services such as Amazon Web Services (AWS), Salesforce, Microsoft Azure, etc. A Big Data Analyst also has to display a high level of Tableau, Hadoop, Spark, MongoDB, and Cassandra.

The market outlook on Business Intelligence and Data Analytics careers is very positive. The coming years are bound to be driven by data and data-driven business decisions. This scenario is bound to make niche workers who specialize in business intelligence and data analytics inevitable and indispensable. Professionals must recognize this trend early and upskill themselves to fill in the talent gap in the industry. Our M. Tech, MBA and LLM Programs are designed to address this talent gap in the industry and make professionals future job-ready.