Data profiling and remediation of poor quality data requires extra manpower to build, extra thought and planning to determine what metrics to use, extra software to make it happen. Why bother?

Our CTO, Mike Hoskins, is known for putting fairly esoteric concepts into plain language, so I sat him in front of a camera a while back, and asked him to answer the question, “What is Data Quality?” Rather than go heavily into what data quality was, he talked more about how we find data quality problems and what problems are the most difficult to tackle.

What is data quality? There are several decent definitions of data quality already out in the world. I will happily add my own to the mix, but it seems like the definitions that make the most sense are more about what data quality isn’t than what it is.

One of the keys to successful data integration is taking the time to ensure data quality across business processes. However, few organizations have the patience or can afford the expense associated with attaining a sufficient level of data quality to ensure effective data integration. Pivotal Information Technology (IT) is employing Pervasive Software’s data quality and [...]

Just as David Loshin pointed out in his recent post: “Data Quality Management: Problems and Horror Stories,” you can bump into data quality snafus in unlikely places. At least, I didn’t lose the Mars lander.