I’ve always felt a little fuzzy about the difference between analytics, business intelligence and business analytics.
It seems there’s good reason for that: You’ll discover quite a bit of variance in how they’re defined, as a recent InformIT post shows.
The piece is actually a chapter from “Business Analytics Principles, Concepts and Applications: What, Why and How,” by Marc J. Schniederjans, Dara G. Schniederjans and Christopher M. Starkey. The chapter sets out definitions for each of these terms, starting with the more general term, analytics.
In short, analytics is an umbrella term for any of the approaches you might use (e.g., data mining, statistical techniques, research methodologies) to explore, visualize, discover or communicate any trends or patterns in the data. The term analytics isn’t a business term per se, but is used across disciplines. Your weatherman probably runs a lot of analytics to give you a two-minute forecast.
Analytics can be:
- Descriptive, which is like a chart or graph that shows you what’s in the data set.
- Predictive, which identifies trends and relationships that aren’t easily seen just by graphing the data. You’ve probably noticed a lot of buzz right now about using predictive analytics with Big Data.
- Prescriptive, which combines data analysis with management and decision science to help you figure out how to use resources, such as your marketing budget.
What, then, is business analytics? Business analytics brings together all three types of analytics in combination to (hopefully) illuminate better leadership decisions. It’s what businesses hope will turn data into strategic advantages. If that sounds like marketing mumbo jumbo, here’s the more academic definition:
“…business analytics (BA) can be defined as a process beginning with business-related data collection and consisting of sequential application of descriptive, predictive, and prescriptive major analytic components, the outcome of which supports and demonstrates business decision-making and organizational performance.”
Like I said, it combines all three types of analytics to help you make better decisions.
That brings us to business intelligence (BI), which is probably what most people are familiar with in terms of tooling. You may think of BI in terms of querying and reporting. Actually, BI is the broadest of the terms, since it incorporates analytics, business analytics and, of course, information systems. The main difference is that BI incorporates storage, whereas neither analytics nor business analytics worry about where the data’s stored.
It’s easy to see why so many tech publications use these terms interchangeably, but if you’re talking with vendors or consultants, it’s helpful to understand where one begins and the other ends.