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May 30, 2008

What it takes to have a QUALITY data quality solution

Filed under: Data Quality — Alena Semeshko @ 4:18 am

There’s really no universal criteria for selecting a data quality provider/solution, it’s rather personal for each company. Before looking at different providers the smart thing to do is to decide on the list of priorities to look for in potential solutions. Some give priority to accuracy, others find execution time the most critical element.

Andrew J. Brooks, wrote a post in his blog on discussing his top three must-be’s for a data quality solution. Come to think of it, I wouldn’t argue with his top-3. It’s Engineered - Understood - Trusted. I’ll look at them step-by-step.

1) What he calls engineered, I’d rather call integrated actually.

It’s about making data quality management an integral part of your architectural design principles; it’s about culture change and cannot be solved by buying a tool.

The solution needs to be fully integrated into all the work processes and become a part of the company’s overall strategy and performance.

2) Understood.

Having accurate, complete, relevant meta data, reference data, master data – call it what you will, is one hell of an obstacle that many have thought about, and most have failed at.

So, a more organized approach than many companies have would definitely work better.

3) Business Trust.

Without business trust, no amount of data profile reports will ‘make’ the business use your data for decision making.

Trust, that never really occured to me. Focusing on your data and leaving out networking and building trust-based relations with the business players around you, as a lot of companies tend to do, is definitely the approach that lacks wisdom.

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