Computer Science vs. Business Analytics

I’ve been asked enough times by current or prospective students about how the Business Analytics concentration in the business school compares with Computer Science (C.S.) that I thought it was time to post about it to make the answer easily accessible. I will first give (very terse) definitions of C.S. and Business Analytics, and then compare them.

C.S. is the science and art of writing high-quality code, usually to solve problems or build applications at a “production quality” level, i.e. good enough to be deployed for many people to use in many ways. (I’m no defining “good”, “quality”, “many”, etc., since that would require a book, not a post; I’m also ignoring the hardware side of C.S.)

Business Analytics (as the very name implies) is designed to give people headed into a business career the tools to consume data and make better business decisions. These skills are critical in any data-driven industry, e.g. finance, marketing, retail, logistics, sports, etc. (I personally think it would be foolish for anyone to pursue a career on the business side of any of these industries without acquiring the skills that the Business Analytics concentration provides. As one director in a top financial firm put it to me, “Python is the new Excel.”)

In terms of how they compare to one another, consider the following analogy: a writer of fiction and a scientist writing a research paper both use the same exact tool, i.e. the written word. However, it is not meaningful to ask which written work – a given novel or a given paper – is “better”, since they are fundamentally different in nature. Similarly, a computer scientist and one who studies business analytics may both write code, but the nature and use of their code are as far away from one another as the scientist’s paper and the writer's prose are. (This analogy does break down when one considers if one person could or could not do the other’s job if necessary, since the analyst’s coding skills are a tiny subset of those of the software engineer, but for purposes of a post the analogy is “good enough”.)

One who studies business analytics is acquiring a critical business skill, i.e. the ability to make well-informed data-driven decisions, and is not different in kind from someone who mastered Excel 20 years ago. (And, as an aside, the strengths and dangers of user developed applications have not significantly changed since Excel spreadsheets began to be shared around businesses so many years ago.)

One who studies computer science, on the other hand, is learning how to create high-quality software of all types and in all contexts, from end user applications (e.g. Photoshop) to internet-scale web sites like google.com to high frequency trading systems to cyber warfare tools to self-driving cars, etc.

The bottom line is that business analytics and computer science are both great things, but have very little to do with each other in terms of career paths. If one wants a career as a business person in any data-driven industry, it would be foolish not to study business analytics. If one wants to be a software engineer of any type, one must study Computer Science.

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