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December 06, 2007

Start small with monitoring, but always think big to achieve data quality goals

Posted by Tom Golden in: Data Quality > Best Practices ; Data Quality ; Data Quality > Management ; Data Quality > Monitoring > Metrics ; Data Quality > Monitoring ; Data Quality > Monitoring > Scorecards

Tom Golden
I attended my first parent-teacher meeting the other day for my five-year old daughter. Another one of those “life stage” events done and dusted – I remember dreading the annual meeting when I was a kid. The notion of my parents and my teacher comparing notes on my behaviour was too much to bear – somebody was eventually going to put two and two together and find out I was up to no good.

It all got me thinking about a recent blog post by my esteemed colleague Garry Moroney. His post Mobilizing the Data Quality Army outlined the level of effort, thought and planning that the US Department of Education is putting into data quality.

As Garry points out dealing with data quality in a large, disconnected organization such as the US schools system is not a trivial exercise. But if you were to only read that one post you might be overwhelmed by the potential size of the data quality task in front of you.

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March 30, 2007

Fit For Purpose Data

Posted by Garry Moroney in: Data Quality ; Data Quality > Monitoring > Metrics ; Data Quality > Monitoring ; Data Quality > Monitoring > Scorecards

Garry Moroney
These days, savvy business executives understand that a report or analysis on their customers, markets, products or anything else is only as good as the data used to compile it. There is always a risk that the data used in the report may not be of sufficiently high quality. Similarly, business partners realize that integrating their systems with another company’s will only add value if the data flowing through the integration meets the required standards.

So more and more the message that data consumers are giving to data providers is: “before I accept this data from you, before I use it in my decision making processes or write it into my systems or pass it on to another party, prove to me that this is high quality data. Prove to me that the data is fit for purpose.

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