The current media coverage of the well-worn "lipstick on a pig" colloquialism got me thinking about some BI environments I've seen in the past year. You be the judge.

"We have a fully-integrated, enterprise data warehouse." But co-located data doesn't mean integrated data. Just because you've got data from different source systems or multiple subject areas on the same physical hardware platform doesn't mean you have an integrated data warehouse. It just means that you have lots of hardware. Calling a big data dumping ground an Enterprise Data Warehouse is like calling a flannel nightgown evening attire.

"We have data quality standards at the corporate level." But that's only because everyone in the corporation has his very own standards. Often data standards are only as valid as the knowledge of the application development team creating them. True enterprise standards mean that the business is involved in defining terms and policies. It means data governance. Anything less is like putting whipped cream on a cow pie.

"We have a data profiling tool and we use it all the time." Fair enough. But your data profiling tool is SQL and it's taking you ten times longer to figure out whether the data is valid than it would with an automated tool. Of course your outsourcing firm is quite happy to continue the SQL-slinging since it involves more billable hours and ongoing work. Now they're talking about manual cross-system data comparisons. Yes, with SQL. That's like putting a long-tailed cat in a rocking chair factory and calling it a pet.

"We have a new metadata project, and we're calling it EIM." Enterprise Information Management is all the rage at companies that are starting to understand that data management is bigger than the data warehouse and that it transcends organizations and systems. But calling a metadata, data quality, or data governance effort EIM is like... Well, you know.

P.S.: For the right way to launch EIM, check out the SAP/Business Objects webcast on Tuesday, September 16, in which Baseline Consulting's Frank Dravis will define EIM and--in advance of his upcoming white paper on the topic--discuss the importance of an overarching EIM strategy. Register here.

Technorati tags: Lipstick on a pig; Enterprise Information Management; EIM; data integration; Frank Dravis