I’ve posted a couple of articles at my company’s blog site that reflect my view on data quality efforts:

  • Yes, there is a business case for improving data quality, and I’ve got real business value examples. If you look for real money where you anecdotally know there are data quality problems, you’ll likely find it in high costs of data correction and rework, and savings related to business process improvements that reliable data enables.
  • There are distinct things an organization can do to reap benefits of improved data management and data quality.  (1) Get started in the first place, (2) find the tangible benefits, (3) cross the departmental silos that exist in every large organization, and (4) promote sound data management practices.

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Who would want to be a national health care administrator?  Who would want the responsibility for managing health care and formulating health policy for tens or hundreds of millions of people?  It seems obvious that such decisions would rely on quality data.  A recent interview impressed upon me how much data managers can learn from a field where data recording millions of separate life and death decisions aggregates to support decisions on the future allocation of health care resources.

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Recently there has been a long, and very interesting, discussion of do-it-yourself versus third-party metadata tools on LinkedIn’s TDWI BI and DW discussion forum (membership required to follow the link). I have followed but haven’t commented, but I suppose I contributed when Information Management kindly published my article on DIY metadata.

The discussion is extremely informative, presenting the views of a variety of knowledgeable professionals in different situations, and describing successful and sometimes not-so-successful efforts to solve the essential metadata challenge: how to document what information is locked up in databases. Continue reading »

 

Information Management recently sent around their pick of best IM blog articles of 2009.  Among them was Forrester’s James Kobelius’s reaction to Bill Inmon’s “incineration of a straw man concept that he refers to as ‘virtual data warehousing (DW).’”

According to Mr. Inmon, virtual data warehousing reminds him of the carnival game called whac-a-mole.  He says “just when you think this incredibly inane idea has died and just when someone has delivered what should have been a deathly blow, out it pops again from another hole.” Continue reading »

 

It is a commonplace to say we should manage data like a resource. But when you think about it, data is an asset but not a resource.  Data isn’t a thing like real estate, employees, or customers, but rather it represents all of those things.  In data-geek-speak, data is a meta-resource that holds information about resources.  That makes data a lot like money. Continue reading »

 

In a recent very thoughtful post on data quality, Paul Erb plays out an analogy comparing data users with Don Quixote and data quality professionals with Sancho Panza, then reverses the analogy to cleverly coin the “Sancho Panza” test of data quality professionals.  He encourages data quality professionals promoting the critical role of data quality to apply a what would Sancho say test to ensure that they are aligned with the needs and interests of data consumers. Continue reading »

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