Data infrastructure optimization, availability & security software
Data integration & quality software
The Next Wave of technology & innovation

A Meditation on Business Intelligence and Analytics

Sometimes, IT terminology is like money. It’s fungible. If a particular term doesn’t resonate with this audience here, we can use it with that audience over there. Or we’ll cook up a different term to mean essentially the same thing. That term doesn’t stir your soul?  How about this one?  Take the terms “analytics” and “business intelligence.” Whichever term we use, we’re often talking about the same thing, right?  Like cash bills, they’re interchangeable.

Or are they?  If we’re really trying to be clear about what we mean, it’s possible to draw important distinctions between the two. Business intelligence (BI) is historical in its import, even if the history is very recent. BI creates a coherent mosaic of events that have happened, hopefully giving us a reasonably accurate picture of the past. A good picture of the past, especially the recent past, can help us in plotting course corrections as we move ahead toward our goals. BI provides answers to ad hoc queries about the present (real time) or past state of things or events.

Then there’s analytics. In the broadest sense of the word, analytics is simply about analyzing large amounts of data, and BI is just one of many subsets of analytics.  In our industry, however, we often see the term used as something almost separate and distinct from BI.  In that sense, analytics carries a future-oriented meaning. Analytics aims to separate the wheat from the chaff, to see patterns that can suggest trends. And trends are definitely predictive.

Apart from the future versus past distinction, analytics and BI each have a different feel — for want of a better term — depending on the circumstances in which they are used.  In a competitive entrepreneurial environment, BI just feels more practical, right? Or, to use a popular buzzword, more actionable.  Whereas analytics feels more general and academic.  It’s like the distinctions that are sometimes made between data, information, and knowledge.  Data are ones and zeroes that describe a thing at any given point in time, whereas information is data that is captured and rendered in some graspable form (whether the grasp is firm or not is another matter), whereas knowledge is what we know in our individual heads about things, or what we think we know.

All very subtle, yes.  So much so that we often ignore the subtleties and use them interchangeably.  In the end, however, distinctions count when we are directing our communications at specific audiences.  And more and more mainframe shops are paying close attention to those distinctions, as indicated in a just-completed survey of large corporations around the world. More than half of those corporations (52%) now rank the use of the mainframe for big data and analytics functions as “important” or “very important.”

Whether companies are looking for analytics or business intelligence, or both, Syncsort recently introduced Ironstream, to make massive amounts of mainframe data easily available to Splunk, without needing specialized expertise and different monitoring systems for zOS

Related Posts