Business Intelligence Quotient

 
 
By Peter Coffee  |  Posted 2003-08-04 Email Print this article Print
 
 
 
 
 
 
 

(B)IQ means understanding the business, not understanding the business systems.

There is a vital distinction between business intelligence and other aspects of data processing or productivity application development. The difference lies in the benefit of identifying changes in business opportunity or challenge, rather than merely meeting business needs.

In this package, eWEEK Labs examines several products aimed at helping enterprise users ask important new questions rather than merely answering familiar questions more quickly and in greater volume than before.

Its not hard to imagine need-driven problems easily dominating an IT architects agenda. However, consider what can happen when enterprise IT addresses only the kind of information that flows as a byproduct of ongoing operations.

For example, a vendor of recorded music that sees slower growth or even a decline in sales might take prompt action to limit the growth of inventory while waiting for a general economic recovery to trigger an upturn in demand. After all, thats whats always happened before. Inward-looking IT architects at that company might even call this a victory for enterprise data processing.

Meanwhile, another record company might also be gathering data on the total amount of time that people spend listening to music and might see listening time on the rise even while CD and tape sales were declining.

The second company would have a head start on identifying the potential competition of online music delivery, while the first would merely be executing a going-out-of-business strategy without even realizing it.

Only one of these businesses is both gathering intelligence (what might be defined as information gathered concerning potential threats) and displaying intelligence (which many might call the capacity to acquire and apply knowledge so as to adapt to changing circumstances).

The core of a BI approach is that it is driven by understanding of the business rather than understanding of business systems. Given that difference, there are additional differences in BI products that eWEEK Labs examines in the accompanying reviews of current tools.

Informatica Corp.s PowerAnalyzer 4.0 (see review) begins with the core belief that information democracy is an organizational immune system—that making common facts available to the largest possible number of people, and letting different groups view those facts in different ways, is a means to avoid selective perception and deliberate deception. PowerAnalyzer is a large system, but it strikes an exceptional balance between open-ended flexibility and usefully structured design.

QlikTech International ABs QlikView 6 (see review) is a Windows-centric data presentation and analysis framework that offers developers high leverage in combining and offering data from many sources to nonexpert users. Developers will have to decide if that leverage is worth the initial learning hump of a new scripting language and other facilities that duplicate features of other software—such as Microsoft Corp.s Office—often already at hand.

Information Builders Inc.s WebFocus 5 was updated with new data visualization tools just as we were completing this package, preventing a full review, but we offer a preview of its superb data visualization tools that we compiled during an online walk-through with Information Builders developers.

With graphical tools that are much more than eye candy for senior management, WebFocus 5 fulfills the BI promise of putting peoples brains into the data processing loop, combining the human strength of seeing the unusual with the machine strength of repackaging data in pursuit of the underlying cause.

We also offer comments on KXEN Inc.s KXEN Analytic Framework, which we believe will change the role of predictive model building through its ability to construct and redesign such models on the fly. This can add an important dimension of value to business applications such as customer relationship management that are notorious for drowning users in data more quickly than they can use it.

KXEN makes the model-building process almost as quick and intuitive as a spreadsheet recomputing simple sums of numbers. With the potential to move modeling out of the statisticians back room and up to the front line of the organization, KXEN is another example of the genuine value to be found in a BI approach.

The notion of BI as a strategic process, demanding support from continually improving technology, certainly strengthens the hand of IT vendors. A well-hyped BI pitch can convince volume IT buyers that they always need not merely more IT than they had last year but also more than they expect their competition to have next year.

From what eWEEK Labs has seen in the products reviewed here, however, theres more than just vendor self-interest behind the BI label—its a perspective from which the opportunities of network-accessible data and standards-based Web services can bring a lot to the bottom line.

Developers will do well, however, to consider a full spectrum of unconventional BI tools like those from Enkata Technologies Inc., whose text analysis and unstructured-data mining technologies can help keep the big picture in sight. Theres much more to BI than just numbers.

Technology Editor Peter Coffee can be reached at peter_coffee@ziffdavis.com.

 
 
 
 
Peter Coffee is Director of Platform Research at salesforce.com, where he serves as a liaison with the developer community to define the opportunity and clarify developers' technical requirements on the company's evolving Apex Platform. Peter previously spent 18 years with eWEEK (formerly PC Week), the national news magazine of enterprise technology practice, where he reviewed software development tools and methods and wrote regular columns on emerging technologies and professional community issues.Before he began writing full-time in 1989, Peter spent eleven years in technical and management positions at Exxon and The Aerospace Corporation, including management of the latter company's first desktop computing planning team and applied research in applications of artificial intelligence techniques. He holds an engineering degree from MIT and an MBA from Pepperdine University, he has held teaching appointments in computer science, business analytics and information systems management at Pepperdine, UCLA, and Chapman College.
 
 
 
 
 
 
 

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