Business intelligence (BI) vs analytics: Today, these two terms are pretty much used interchangeably. They both generally describe the practice of using data to make better business decisions.
But are they actually the same thing? Should we be treating these terms as synonyms?
Customers are demanding modern analytics capabilities in the applications they use every day. But what are the product teams behind those applications calling these features: BI? Or analytics?
Here, I offer up my definition of these two terms and outline the similarities and differences.
Business Intelligence (BI)
BI has largely come to represent a set of technologies that support decision-making within enterprises focusing primarily on executives, middle management, and the analysts who support them.
While there is a lot to a BI technology stack, the main outputs are dashboards (for executives), reports (for managers), and pivot tables (for data analysts). Recent trends, like self-service analytics, are aimed at making it easier for the end consumers to produce these outcomes with less help from technical staff like IT.
Barry Nicolau of Signeture Solutions says, “Many of my customers are business decision makers, and they don’t want to have to wait a week for IT to give them a specific chart or calculation.”
To define analytics, it helps to first define “analysis.” Analysis is the process of breaking something down into its constituent elements for the purpose of understanding the whole.
To me, analytics, then, is the broad set of tools by which that process is supported—particularly where data is used to conduct the analysis.
Where does that leave BI? It becomes a subset of analytics, or one narrow approach of analytics. (It’s kind of like how a square is a rectangle, but a rectangle isn’t a square.)
Business intelligence, I feel, is well-defined. I can get large groups of people to consistently look at something and agree if it is or is not BI. Analytics, on the other hand, spans much wider: Google Analytics, R, spreadsheets, building a travel budget for a trip to Europe on a piece of paper, IBM Watson—the list goes on.
How to Differentiate Between Business Intelligence and Analytics
So which one is or is not analytics? The terms “analytics” has roughly the level of agreement as the term “lunch.” We know roughly what it is, but the variations are so wide as to make the term not very useful. You can’t say walking down the street eating Pocky “isn’t lunch,” because it could be.
Can you use these terms, business intelligence, and analytics, interchangeably? Sure, the majority of the time, people are going to know what you are talking about. And regardless of what you call it, your product needs it to stay modern, drive adoption, and reduce ongoing requests to IT for information that will help your customers do their jobs.
But if you really want to differentiate, here is when I think you should use BI vs analytics: Use the term “business intelligence” if you are doing the stuff to produce a report, dashboard, or pivot table for an executive, middle manager, or analyst. And use “analytics” when you move past basic BI capabilities and use information and data to help your customers become highly effective at getting a job done.