APR 19, 2011 4:54pm ET

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I had an interesting conversation with a young participant at the February, 2011 Strata Conference on “data science” during a break in first day action.

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Comments (8)
Quick approximations are useful in business terms but only as indications and not absolutes upon which critical decisions should be made.

The real risk with approximations is that speed becomes more important than accuracy - at which point the budget for Master Data Management and all forms of robust quality governance are cut because the perception is that accuracy is no longer a business requirement.

Posted by Geoffrey P | Wednesday, April 20 2011 at 10:07AM ET
A business needs both. The critical piece is to make the best approximation given what is known about a problem. The shift I am seeing / managing is to move away from the typical enterprise wide approach of MDM when the answer is "good enough". This is where flexible architectures enter the picture enabling the business to work with messy / imperfect data as answers to typically messy questions are being asked. Product development is a great example of an area where the majority of data available is birthed as an estimate / approximation.
Posted by Rich C | Wednesday, April 20 2011 at 10:30AM ET
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