Sean Crowley
Lean Manufacturing in the Data Warehouse Factory – Building Trusted Data
Lean manufacturing, as defined by Wikipedia, is “a production practice that considers the expenditure of resources for any goal other than the creation of value for the end customer to be wasteful…Essentially, lean is centered on preserving value with less work” and is a management philosophy derived mostly from the Toyota Production System (TPS). I’ve been having discussions with Jim Harris from OCDQ Blog and Reuben Vandeventer, Director of Data Governance for CNO Financial and others about best practices for data quality management and the applicability of lean management practices as it relates to data warehousing. Click here to hear Jim, Reuben and I discuss three critical areas of data quality to focus on for building data warehouses that people actually use and trust.
You Want the Truth? You Can’t Handle the Truth!
So, I’m a complete sucker for the courtroom scene in the Rob Reiner film “A Few Good Men” for a number of reasons: it was written by Aaron Sorkin (loved West Wing and Sports Night), it’s a classic Jack Nicholson scene, it is one of Tom Cruise’s roles where he actually does some acting, and it’s a great 6-degrees of Kevin Bacon movie (I mean, it’s got people from Demi Moore to Cuba Gooding Jr. to Kiefer Sutherland, to Noah Wylie – think of the connections you could make with just those actors). I get sucked into this scene whenever I click by it on the television. (more…)
Data Quality Goes Green in Colorado, and on the Informatica Marketplace
A recent trip to a supermarket in Telluride, Colorado struck me as a funny place to find an analogy for data quality, but there it was. You see, supermarkets here require you to bring your own bags to cart your groceries home. Those brown disposable plastic bags are banned here – the town has made a firm commitment to the philosophy of Reduce, Reuse and Recycle. By adhering to this environmental philosophy, data integration teams can develop and deploy successful data quality strategies across the enterprise despite the constraints of today’s “do more with less” IT budgets.
In the decade that I’ve been in the Information Management space, I’ve noticed that success in data integration usually comes in small increments – typically on a project by project basis. However, by leveraging those small incremental successes and deploying them in a repeatable, consistent fashion – either as standardized rules sets or data services in a SOA – development teams can maximize their impact at the enterprise level.
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