I’ve worked with health care data for the past few years, and in a recent conversation I realized it might be valuable to detail some of the complexities of health care data for those who might enter this growing field. Of course these considerations aren’t unique to health care, but they are typical of the challenges that the new health care application developer or analyst might face. Continue reading
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