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 »
A recurring theme in the literature on IT over the years has been frequent failure of IT projects. Most studies lay the bulk of the blame on requirements (examples here and here). One way to improve accuracy and fit-to-purpose of requirements, and thereby promote project success, is to include data analysis as well as process analysis in the requirements plan.
I’ve cited here the need to start data interface analysis early to avoid budget and schedule blow-ups when, as a result of not thinking early about interface complexity, data integration work turns out to be bigger and nastier than anticipated. 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 »