Master Data Management Grows Up, the Finale: Big Data

    This week, I’m looking at the way new trends such as social media and cloud are causing MDM to grow up. Today, let’s look at what may trigger the biggest shift for MDM: Big Data

    Why do I say that? Because it turns out, applying master data management to Big Data may be less about MDM and more about a paradigm shift in how we think about and use MDM.

    Although there are different ways to approach MDM, it’s often seen as a repository for master data. All the data is dumped into MDM for sorting, cleansing and achieving that mythical “one version of the truth.”

    But Big Data will change that, because, frankly, Big Data is too big and changes too fast for that to work, according to Steve Jones, the global lead for master data management at Capgemini, during a recent Q&A .

    “Really, we don’t see the next generation of MDM being like the old generation of MDM,” Jones explained. “Historically, MDM was around the customer repository. That’s just not feasible in the world of Facebook and Twitter.”

    Information is federated, so the next generation of MDM will be about mastering the core, he added.

    In effect, you’ll need to think less about MDM as a repository and more about MDM as a way to govern global information, experts say.

    Jones isn’t the only one who sees this as the key role for MDM in a Big Data world.

    John Radcliffe, a Gartner research vice president, also said MDM programs will ultimately need to “govern the relationships” between internal data and Big Data from external sources, according to TechTarget.

    Although I talked about social MDM earlier this week, it’s important to remember that much of the Big Data companies want to use is from social networks. Radcliffe said it’s impossible to use MDM to govern this external data; instead, use MDM to link internal master data files to external social network profiles so you can learn more about your customers.

    Forrester analyst Michele Goetz also talks about MDM requiring a “reboot” for Big Data.

    Although she focused more on what that means when you’re dealing with the unstructured nature of Big Data, it’s clear governance is a key part of that when she writes, “Because data has moved beyond structured and relational database constraints with big data, MDM must account for the structure and enforce business policies for a trusted holistic view.”

    Obviously, MDM done well has always had governance as a key component, because a good master data management program will cover who owns data and who has the authority to alter it; otherwise, the data is fixed briefly and then becomes outdated or the conflicts reappear.

    But Big Data puts even more demands on MDM as a governance tool, because there’s so much data, the focus shifts from just adding it to filtering out what’s usable and useful to the business.

    Of course, the future of MDM is not all philosophical changes.

    Jones describes the next generation of MDM tools as having characteristics of a service-level agreement infrastructure, with MDM offering a cross-reference of data and control of the core that matters. He also said MDM will need a data integration infrastructure — which, really, is already a part of most MDM solutions — to create and share that whole view as needed.

    “Really, it’s about shifting the information when it’s required and providing that identification, less than the historical view of effectively a digital landfill of data into which everybody poured everything,” he said.

    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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