An XML schema, if used, would help provide some additional meaning. Data types could be defined for each element and namespaces could provide context. The <documentation> tag could provide a basic description of the object. Traditional data models and metadata repositories, however, break down “documentation” into many more levels of granularity: such as description, notes, security level, steward and lineage.

Such additional information might clarify that the above location is a top-secret military base, used by the air force and defined by the Central Intelligence Agency, noted that this location was changed in 1992 based on organizational changes in power, and that the source data came from two military databases joined with specific transformation rules.

To put this in context, it helps to refer to the famous - or infamous, depending on your view - long tail. In this case, with an infinite number of contributors and consumers on the web, the volume can be much larger in the tail than in the head of the curve. The same paradigm can be applied to data management.

As noted earlier, data management has revolved primarily around the closely controlled, high-volume database systems - the head. With XML, data can be accessed and manipulated by a large number of internet collaborators – that’s the long tail.

So what’s the risk of loosely managing the long tail, as long as the head is closely controlled? Take an online retailer whose website content is normally driven by a database system managed using the traditional approach, that can now be accessed and transformed via the XML technology stack to a larger audience.

That’s clearly a risk if a retailer doesn’t understand its location information. Now, though, you’re mixing that with Google maps with craigslist.com, and the divergent definitions of location information will cause an error and - in the worst case - your delivery winds up at the wrong house.

This matters even more when those in corporate management start asking to ride the mashup wave and/or obtain quick, pretty reports that haven’t been validated by a data governance team. The slick mashups their teenage whizkid can whip together at home may not be appropriate for their corporate reports. Regulations like Sarbanes-Oxley require the strict governance and data lineage reports that the traditional approach can provide.

As in many areas of life, then, while the new generation has some great ideas and innovations, they also have much to learn from the tried-and-tested lessons of their forebears. ®

Donna Burbank has more than 12 years' experience in data management, metadata management, and enterprise architecture. Currently leading the strategic direction of Embarcadero Technologies architecture and modeling solutions, Donna has worked with dozens of Fortune 500 customers worldwide and is a regular speaker at industry events.

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