In my last post, I pointed out that we data quality practitioners want to apply data quality assertions to data instances to validate data in process, but the dynamic nature of data must be contrasted with our assumptions about how quality measures are applied to static records. In practice, the

It’s common at the start of a new year to create a long list of resolutions that we hope to achieve. The reality, of course, is by February those resolutions will likely be a distant memory. The key to making any resolution stick is to start small. Create one small

After working in the data quality industry for a number of years, I have realized that most practitioners tend to have a rather rigid perception of the assertions about the quality of data. Either a data set conforms to the set of data quality criteria and is deemed to be acceptable

As this is the week of Christmas, many, myself included, have Christmas songs stuck in their head. One of these jolly jingles is Santa Claus Is Coming To Town, which includes the line: “He knows if you’ve been bad or good, so be good for goodness sake!” The lyric is a

We've explored data provenance and the importance of data lineage before on the Data Roundtable (see here). If you are working in a regulated sector such as banking, insurance or healthcare, it is especially important right now and one of the essential elements of data quality that they look for