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What You Don't Know Can Hurt You

Semantics take us from ones and zeros to understanding.

We're about to lose a great customer: That dire warning would flash red and sound the buzzers in the minds of most sales, service and other business managers. They'd want to take action. What's the right thing to do? How much business does this customer do with us? What guidance do our stated strategic business objectives give us as we fight to win this customer's heart, mind and wallet?

Particularly in organizations that have grown through mergers and acquisitions—and we can include the embattled US Department of Homeland Security here—figuring out the right action to take is a journey thwarted by many blind alleys full of surprises. That is, if decision makers ever get the dire warnings: With shareholders, regulators and politicians demanding executive attention, customers can easily go out of focus.

Letting the data speak, business intelligence (BI) tools reveal clues through analysis and reporting of largely historical data. Performance metrics build on BI and other applications to give guidance about the customer's apparent worth in terms of market share, revenue, sales commissions and other factors. Certainly, it's an incredible accomplishment deriving such decision-support information out of a typical stream of transactional updates.

But how do you get from ones, zeros, cold numbers and metrics to a blunt, natural-language statement that everyone understands? As we discuss in this issue, users of current BI and unstructured content management tools are frustrated with data and information integration difficulties. "Single view of the truth" has become a rallying cry in both IT and user communities. Customer intelligence, regulatory compliance and numerous other imperatives compel organizations to break down silo walls and bring all the information about an object of interest into a single view.

Yet, as Neil Raden notes in our cover story, single-view partisans have to be careful not to shave off everything that's interesting about information as they conform the pieces to the necessities of integration. That's a big reason "semantic" integration, which focuses on uncovering meaning largely through the relationships between items of information, is growing in importance. Semantic Web standards, fast becoming critical to search engines, may help IT bridge the gap between traditional BI and simple statements that everyone understands, no matter what their business function.

"In the traditional database realm, there's this unspoken belief that if it's not in the database, it doesn't exist," says Dave McComb, author of Semantics in Business Systems (Morgan Kaufmann, 2004). "The 'open world' principle, which is big in semantics, says that your inferences and reasoning must assume that you don't know everything." Citing clinical drug trials as an example, McComb notes that "not getting a row of data back doesn't tell you what you really need to know, which could be why some people were eliminated from the trial, why others were included and why other critical information isn't there."

In other words, users of the BI "stack," which includes data integration tools, data warehouses and the databases themselves, have to be mindful that important information exists outside the database—and outside their hard-won single view. Content integration will add new data sources from which to draw more varied understanding and link insight with business processes. But without semantics, organizations will remain blind to meaning—and to the unknown motivations behind customer behavior.

David Stodder is the Editorial Director and Editor-in-Chief of Intelligent Enterprise. Write to him at [email protected].

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