Data Quality – is “close enough” “good enough”?

I was discussing the data quality vendor landscape with a colleague the other day and he drew a very interesting parallel, an analogy about solutions and performance I hadn’t heard before. Frankly, on the surface it was almost comical—but the more I thought about it, the more I realized the significance. For some reason, too often technology buyers…
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6 Reasons Companies Ignore Data Quality Issues

Be it lean startups or multinational enterprises, true, proper maintenance of data quality gets swept under the rug. The initial efforts put in place early-on aren’t matched with best practices in the long run. Managers may be tempted to leverage existing CRM platforms tools to try and meet the data cleansing needs – not knowing that these solutions fall sorely short of any kind of proper record cleansing. While budgets are emptied in favor of customer acquisition and advertising spend, these half-hearted attempts at cleaning house leave valuable customer records collecting dust, hidden in plain sight.
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Creating Your Ideal Test Data

Every day we work with customers to begin the process of evaluating helpIT data quality software (along with other vendors they are looking at). That process can be daunting for a variety of reasons from identifying the right vendors to settling on an implementation strategy, but one of the big hurdles that occurs early on in the process is running an initial set of data through the application.
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