Business Analytics vs. Data Science

If you open any business journal or newspaper, you are likely to see headlines that include the terms "business analytics" or "data science." Many articles seem to use these terms interchangeably, but are they really referring to the same thing? What do these terms mean, and what is the difference between the two? This post will help answer those questions.

Data Science

Data science is focused on developing problem-solving methods and tools to bring meaning out of data. At the core of data science is a statistical and programmatic approach to create and use algorithms to extract meaning out of data. The focus of each algorithm has a specific type of problem in mind that can be applied across multiple fields. For example, a common algorithm like multiple regression can be used to understand the relationship between one variable and a set of other variables. It doesn't matter to the data scientist if those variables are related to the hard sciences or to application areas like business.

Business Analytics

Business analytics is the application of data science methods and tools in an attempt to answer a business-related question. At the core of business analytics is a statistical approach to solving problems. One way to use statistics is to describe the current state of the business (i.e., descriptive analytics). For example, we may want to know the average revenue generated per salesperson over the past fiscal year. The average is a "statistic." Another way to use statistics is to predict what the future might hold for a business scenario (i.e., predictive analytics). For example, a business might want to predict the profitability of its product line next year, based on a few assumptions they have about their potential market. One other way to use statistics is to recommend a specific choice when confronted with a business-related scenario (i.e., prescriptive analytics). For example, a business may want to streamline their production flow in a manufacturing facility.

The Difference

Based on the definitions offered above, we can say that business analytics is really just the use of the tools created by data science in the business world. Where it can get confusing is that those doing business analytics can sometimes dive down into the weeds of data science to tweak the algorithms for more efficiency, and those who do data science can sometimes apply their algorithms to business-related scenarios. In the end, the two fields are heavily related but generally differ based on the level of focus.

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