Customer Executed Data Quality

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Google Image Labeler logo

I was intrigued to hear that a couple of weeks ago, Google finally killed off their ‘Image Labeler’ game/service/tool thingy. I remember back in 2006, when it first arrived as a ‘beta’, thinking it was another piece of genius from those clever chappies at the Googleplex. Managing to subtly get their own customers to improve the quality of their image catalogue’s metadata….for free….by thinly disguising it as a game….Genius! Continue reading →

Cutting Loose

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I’ve been catching up on some blog reading recently and have just read Dylan Jones’ article which was posted on the Data Roundtable website at the start of September. In it, Dylan explains that the reading of ‘Touching The Void’ by Joe Simpson sparked his thinking about root cause analysis and the approach companies take in tackling data quality. When I started reading the article I actually thought Dylan (@dataqualitypro) was going to go in another direction and use the analogy of ‘cutting loose’. He didn’t, so I will :-) (hope you don’t mind Dylan!).
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Solvency 2 – FSA Data Quality Expectations

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Back in February the FSA published their Internal Models Approval Process (IMAP) Thematic review findings, a paper that brought together their collective findings after a period of discussion and probing of a number of insurance firms. The intention of this paper was to use the information to help identify the better practices being employed by firms, to help the FSA better understand the areas discussed and to give firms some much needed gen into the FSA’s thinking as they approach the pre-application phase of the IMAP.
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