The difference between data science and business analysis

DETROIT – In various business environments today, the term data science seems to carry with it a particular misunderstanding, for which it seems to be mistakenly equated with business analysis. This notion is further inflamed by companies and organizations that make the mistake of defining these roles and using them interchangeably. This has led to data science being the most widely known concept, despite having its definition blurred. To remedy this, you need to identify and understand the fundamental difference between data science and business analytics, so let’s get to the point.

What is data science?

Simply put, data science is the use of various fields such as mathematics, statistics, algorithms, and technology to study data, extract valuable information, and prepare data for analysis. Data science also includes analyzing collected data such as web and cellular data to obtain actionable data-driven information. Individuals who practice data science are called data scientists and, in a corporate structure, their primary focus is on using data to find solutions and predict outcomes for the business.

The role of data science in a company

When the data is processed correctly, it is a boon to all businesses, as it makes a difference in the success of the business. The reason is that most companies manage large volumes of data or big data that cannot be managed by the usual traditional business tools. Therefore, to sort big data and extract meaningful and actionable information, the company would need a data scientist. The data scientist would be tasked with collecting, analyzing and interpreting data, as well as formulating theories and looking for patterns in the data.

What is business analytics?

On the other hand, business analytics consists of using data analytics, statistical models, and other quantitative models to solve business problems. It acts as a bridge between business and information technology, as it consists of a deep understanding of the business and a deep understanding of data and statistics, using both aspects to provide data-driven recommendations for businesses.

The role of business analysis in a company

Business analysts act as the link between business and IT services, especially as they use data analytics to produce insights and make business choices. As a result, business analysts work at almost all levels of a company, with tasks that include setting project goals and objectives.

Key differences between data science and business analytics

  • A key difference between the two is in the structure of the data. While data science primarily uses unstructured data and structured data when needed, business analytics needs structured data.
  • Data science is a superset of business analytics, and a data scientist can easily switch to business analytics, but the reverse isn’t the same, as a business analyst will have to learn a lot to get through.
  • In the practice of data science, there is a need for a lot of programming and generally good computer skills, however, this is not necessary in business analysis.
  • Data science primarily addresses general, unstructured questions with no clear answers, but business analytics deals with specific business-related questions that require direct answers and results.
  • Data science requires a large amount of data to work, while business analytics does not, as they can only work with the business aspect.

If data science is something you are interested in, a data science course is a good next step.


Drawing from the details above, it is clear that there are different and distinct differences between the two concepts, with the fundamental difference in the role they both play. In data science, the focus is primarily on data development, while business analytics takes a more hands-on approach as it has to manage data and derive results from it.

Biography: James Daniels is a freelance writer, business enthusiast, a bit of a tech buff and a general fanatic. He is also an avid reader, who can spend hours reading and learning about the latest gadgets and technologies, while offering views and opinions on these topics.

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