Double Trouble with Social MDM and Big Data

Yesterday was the first day at the MDM Summit Europe 2013 in London.

One of the workshops I attended was called Master Data Governance for Cloud/Social MDM/Big Data. The workshop was lead by Malcolm Chisholm, one of my favorite thought leaders within data management.

According to Malcolm Chisholm, and I totally agree with that, the rise of social networks and big data will have a tremendous impact on future MDM (Master Data Management) architecture. We are not going to see that these new opportunities and challenges will replace the old way of doing MDM. Integration of social data and other big data will add new elements to the existing component landscape around MDM solutions.

Like it or not, things are going to be more complicated than before.

We will have some different technologies and methodologies handling the old systems of record and the new systems of engagement at the same time, for example relational databases (as we know it today) for master data and columnar databases for big data.

Profiling results from analysis of big data will be added to the current identity resolution centric master data elements handled in current master data solutions. Furthermore, there will be new interfaces for social collaboration around master data maintenance on top of the current interfaces.

So, the question is if taking on the double trouble is worth it. Doing nothing, in this case sticking to small data, is always a popular option. But will the organizations choosing that path exist in the next decade? – or will they be outsmarted by newcomers?

MDM Summit Europe 2013

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One thought on “Double Trouble with Social MDM and Big Data

  1. Richard Ordowich 16th April 2013 / 12:59

    The pursuit of master data reminds me of the pursuit of a singularity of the universe. Trying to reduce a person or entity into one representation wastes time and resources. There is no “master” record. There are numerous viewpoints of entities and a solution should represent a network capable of representing these viewpoints as interconnected attributes and flexible enough to reinvent itself into yet another network or viewpoint. If we can’t reach consensus on what is a customer or a product never mind what is a human, how do we expect a database will represent this lack of cohesion?

    Master data management consumes resources in the acquisition and deployment of the solution but what is often forgotten is the investment in ongoing human resources needed to maintain this data far into the future. The technical solutions are limited in what they can automate and much manual work is done cleaning and manipulating the data. That is the Achilles heel of MDM.

    Master data management solutions are “in the box thinking”. The technology constrains the solutions. Time to think of an entity as a network and forget creating a “master”.

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