In last month's column, I discussed the issue of disparate meta data repositories. In that column, I listed the four most common problems created by this phenomenon, and I discussed the first two issues in detail. In review, the four most common problems created by disparate repositories are: missing meta data relationships, repositories built by non-meta data professionals, costly implementation and maintenance, and poor technology selections. In this month's column, I will address the final two problems and discuss why they exist.

Business units and technical groups typically need meta data to properly run their business and IT systems. Therefore, these groups will not want to wait for their company to start building an enterprise-wide meta data repository, assuming that they even have such a project in their current IT plans. As a result, they build disparate meta data repository solutions that are designed to only handle one or two specific problems/challenges. If executive management knew the cost of these meta data repository point solutions, they would see that it far outweighs the cost of a truly sound enterprise-wide meta data management repository. This situation closely follows the path that many companies have taken with data warehousing. For example, the average company needlessly replicates its data warehousing efforts across many of their lines of business, as opposed to centralizing this function. It has been my experience that this approach typically increases the costs of data warehousing by more than 300 percent. These companies could provide all of the data warehousing functionality that they provide today at less than one-third of the cost if they managed their IT systems properly. The types of organizations that build point meta data solutions are traditionally concerned about the cost of building an enterprise-wide meta data repository. However, the cost of this enterprise-wide repository would pale in comparison to the costs of all of the disjointed meta data initiatives that are currently underway or in production (see Figure 1). Doing it right the first time is always less costly than doing it wrong and trying to fix it later.

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