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    When Is Data Quality NOT a Priority? When the Business Says So

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    Sometimes, the business doesn’t care about data quality. It’s a hard thing to hear, but someone has to be honest with you about it, and Capgemini’s Big Data and Analytics expert Steve Jones is stepping up to do it.

    Actually, Jones is talking about master data management (MDM). It’s often confused as a data quality project, he writes, but the primary goal of MDM isn’t data quality these days. It’s really collaboration.

    If that sounds like a major departure from what you’ve read in the past, you’re right. Data quality, along with data governance, has long been heralded as key components to finding success with MDM.

    Jones acknowledges this shift, but notes that businesses are now more concerned with supporting internal and external collaboration. You can thank the cloud and Big Data for that, I’m sure, but his point is that this provides a much different use case for MDM.

    “You need MDM because you are attempting to join across systems and business units,” Jones writes. “So the real value from MDM is that cross reference that tells you who the customer is and where all the information about them lives in the various systems… even if you never clean any of it.”

    He’s also making an important point about data quality—especially when “total quality” is pursued as an end goal in and of itself. Don’t read this as saying data quality doesn’t matter—that’s not his point. Rather, Jones is saying that data quality is now about supporting collaboration.

    That may mean facing the difficult fact that data quality isn’t the top priority, even for MDM. So what does this mean for IT?

    First, give the business some credit. They know which data is dodgy, Jones says. This is particularly true when it comes to Big Data sets, such as external data from social media.

    “Lots of social media is amazingly poor quality, but taken in volume trends can be seen,” he said. “What makes it more valuable though is when you can enable that cross-reference between the high-quality and the lower quality so you can see the trends of your customers and products not just trends in noise.”

    Second, ask yourself why you care so much. Seriously, if the business isn’t worried about data quality, why does IT stress over it so much, Jones challenges.

    “You might think its an absolute disaster that a given attribute isn’t used in a standard way, but it could be that no-one in the business gives a stuff, so tell them about the issue but let them decide if they want to spend the money making it better,” he suggests.

    What if they come back? Well, then you can let them know you’re willing to help them re-prioritize their goals, Jones says.

    Loraine Lawson
    Loraine Lawson
    Loraine Lawson is a freelance writer specializing in technology and business issues, including integration, health care IT, cloud and Big Data.

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