In some quarters, "business intelligence" has apparently gotten a stale reputation and there is a crowd that looks at BI like a bunch of old green bar reports. That's not true of course, and it's wise to remember that hindsight is still our most trustworthy guide as the volume of history grows and time marches on.
But as we go about our business, there is a kind of operational impatience with latency we seem to have picked up from our consumer devices, and a need for environmental awareness that keeps demanding more, faster. I Shazam to know the name of the song I am hearing, I plot my dinner based on the direction I am walking and text my friend to cause our paths to intersect.
We've gussied up plain old business intelligence with adjectives and descriptions and morphed performance management into BI with live visualizations. We have "operational BI," "agile BI," "BI for the masses" and "real-time BI" (unless you prefer "right time BI"). I'm working on a story now that talks about "embedded BI" in a kind of task-oriented way. Part of that is descriptive, part is marketing and part is selling a term people are comfortable with internally.
But it's all okay. One of my favorite definitions of business intelligence came from, I think, a onetime Forrester Research analyst whose name I can't recall. He called business intelligence "the process of making better decisions," and those individual words add up to a lot of meaning.
It's still about decision-making. What's changed is the growing number of tools and rituals in our kit bag. They access and describe different kinds of data in different quantities and latencies and in more or less detail. The toolkits we're using are getting bigger and faster and analytically driven, specific and versatile, and they all have a place in business intelligence.
I joined this company more than seven years ago when a director decided to launch a magazine called Business Intelligence Review, when people started focusing more on the front end of data and reporting tools and the user base for BI was growing. Back then, BI Review was almost a supplement to what was then called DM Review, a magazine for data geeks to discuss the heavy lifting and nuances of data management that was originally the business of the data warehousing crowd.
The smarts of all those people is still the foundation of what they do today. The art of design and data modeling led us to the business related and collaborative data practices like data quality and governance we talk about now. Those same people are doing a lot more than they used to with new tools and ideas built on what they already had learned.
The two magazines morphed back together and more than three years ago we transformed DM Review into Information Management, a title that pretty well sums up much of what we do today professionally and privately.
We're still working on the process of better decision-making. When you do Google "business intelligence" I'm glad to say you'll find the website you are looking at now listed 4th in the unpaid rankings, after wikipedia and an eponymous business intelligence url, and right between Microsoft.com and SAS.com.
A lot has changed, but you guys still know what you are talking about.















In 1984, Kirk Tyson wrote a book called Business Intelligence, in it he defined BI in the in a brilliant way:
"Business Intelligence is a reliable, analytical process that transforms raw data into relevant, accurate and useable strategic knowledge".
What is interesting about this definition is that it does not at all include IT, computers or software. BI was simply a logical process of analyzing and integrating data that started manually and has evolved to exploit the power of technology. http://blog.strat-wise.com/2010/10/10/-why-marketing-finds-business-intelligence-useless.aspx
Regards, Bill
I agree we keep wanting to know more. Understand more. Whether it comes to understanding our business better or our personal lives, it usually requires more data be generated to help understand the problems better. It also requires tools that can be used by the average human in an interactive way. Much as the way you refine your searches on Google to find that exact website you are looking for, being able to refine the questions you ask about your business allows you to approach the problem and refine as you go.
I believe we are experiencing the beginnings of a Big Time Data Revolution. Remember, big data includes large amount of created content like photos and videos, but is also comprised of the traces of our use of that data and applications. Understand and analyzing these data exhaust trails allows companies to gain better insight into their business process, and enable them to optimize their offerings to add value to their end users.
Much as the Industrial Revolution improved the quality of life for all, this modern day data revolution will eventually do the same.