Yet more data quality posts

You'd almost think that Beth and I were the same person - we both seem to post about the same topics at around the same time. Today she posts on the joys of establishing standards in product descriptions, I had intended to write something similar, but instead I write this

Often the biggest problems in data quality projects are nothing at all to do with the technology needed but are to do with people. And those people are not always the technologists involved directly with the work; often it is the information workers spread throughout the organisation. Fixing up these people issues needs a degree of charm and tact from the data architect running the data quality project, oh, and it needs a corporate big-hitter to sponsor the project and to enforce change.

• Common taxonomies need to be established
• Data stewards, or owners, (and these are business people, not IT staff) need to be identified and empowered to maintain specific types of data.
• Where regularity compliance is important (and isn't that everywhere?) data quality processes need to be engineered so that only the right people can make changes and that might mean that the ownership of a item is split on attribute domains - say the financial attributes are owned by an accountant and the physical attributes by someone in supply chain.