There is a bit of a debate taking place about the nature of business analysts -- one that deserves some attention. In a recent article, writer Ted Cuzzillo wrote about "a new breed of business analyst" that is data hungry, determined, and resourceful. The conclusions in the article are drawn mostly from research performed by Lyzasoft, observations of Lyzasoft founder Scott Davis, and researchers at Microsoft's Gemini program. This is a good article that provides some insights valuable to any IT or data management person who needs to work with and support business analysts.

The article drew a somewhat sarcastic response from visualization guru Stephen Few. In his blog, Few accuses Cuzzillo of reporting the obvious and claiming "new" for something that has been with us since the dawn of IT. But Cuzzillo doesn't write fluff. His writing is always informed, considered, and well-reasoned. If you're not familiar with Ted's work take a look at datadoodle.com to get a sense of the breadth and depth of his knowledge and interests. 

Few makes a valid point when he says that "anyone who has ever worked in decision support has been aware of these analysts all along." Aware of them, yes. But its a long path from awareness to what is really needed - understanding, cooperation, and collaboration.

So I suggest that Few (and all of us) would be well-served to look beneath the surface of Cuzzillo's very brief article. There is good stuff under the covers, with Scott Davis as the source for much of that good stuff. Davis is a very smart guy who is closer to the world where business analysts live than most of us. We can learn from him. As an example, here is just a short sample of Scott's insights from an email that he sent me a couple of months back:

"The typical analyst will regularly export multiple BI reports, find a way to integrate the data in them, search for and blend in some supplementary data from an outside source, enrich the whole set with mathematical, statistical, operational, and financial computations -- ALL JUST TO CREATE A SET OF INFORMATION relevant to the question at hand.  To this person, traditional BI technology does not fundamentally change WHAT they do or HOW they do it."

My point is that it doesn't matter whether the analysts that Cuzzillo describes are a new breed or not. IT people in general have yet to accept them as the mainstream of business analysis that they represent. .  

While in the car this morning I heard a great interview with long time journalist Bob Schieffer. Schieffer was at Washington State University - my old stomping grounds - to receive an Edward R. Murrow award for lifetime achievements in journalism. The most humorous line in the interview was a comment that maybe you should worry when receiving lifetime achievement awards -- "Does it mean the end is near?"

But the most thought-provoking line was when Schieffer was asked about Twitter. His response: "It's cute. But it's not journalism." He went on to comment on the distinction between objective facts and editorial opinion, suggesting that in today's world of so much information and so-called news we blur the lines and confuse the two.

The questions that Schieffer's comments raised in my mind are these: Is that same trend occurring in business intelligence? Do we suffer from "intelligence overload" and if so, what can we do about it? Do we skew the facts and bias perceptions with (intentional or unintended) misleading charts and visualizations? Do we leap to conclusions with a few facts and partial truth when analytic systems could show the whole truth?

In short, I think there is still much that we have to learn about how people and information interact and the old-time journalists - those who treated news as information instead of entertainment -  may be a good source of learning. 

I left the TDWI conference in Las Vegas a bit over a week ago with my head afloat in buzzwords. It seems that every quarter there are new terms and that I was not the only person at the conference struggling with the ambiguity and apparent overlap among terms. Maybe its time that we define our terms and differentiate between similar sounding terms.

I've listed below some of the language that stands out as needing clarification. Along with each I have included a tentative description as a starting place for some discussion and clarification. Please weigh in with your thoughts about the meanings of these terms and add to the list any that you believe need similar attention.

• Analytics - Many people use this term to describe analytic tools and the things that they produce (dashboards and scorecards). I think analytics includes the entire process of mathematical and statistical analysis to gain and use insight.

• Embedded Analytics - My interpretation of this term is that it describes analytic capabilities that are tightly coupled with a hardware platform ... the basis of analytic appliances.

• Operational BI - Business Intelligence feedback in the form of reports, dashboards, and scorecards into the operational processes and applications of the business enabling a strong connection between strategy and operations.

• Operational Analytics -  Integration of analytics (see definition above) into operational systems. Operational systems in this context include both planning systems (supply chain, demand forecasting, sales planning, etc.) and transaction systems (order processing, supply chain execution, etc.).

Once again, please comment with your thoughts. Together we can clear the fog.