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The new future: master data governance


Katie Slattery 2 minute read Data governance

A dual process approach to data governance and master data management (MDM) is one that can result in dramatic improvements within any given organisation.

According to Robert Rich, global program director of MDM at Aprimo, by banding the two specialisms together, businesses are creating opportunities that they would not ordinarily come across.

This power couple, as the data expert describes the merger in an article for Information management, is "equal to more than the sum of its parts".

Data governance is quite a broad term in so many ways, best described as the way in which an organisation brings together the overall supervision of various data policies and practices (quality, management, cleaning and so forth).

Gartner best sums up MDM as a "technology-enabled discipline" that sees organisations utilise IT to ensure "uniformity, accuracy, stewardship, semantic consistency and accountability" of its data assets.

Naturally, there is a great deal of crossover, but both are very much independent entities, which specific emphasis on their own key areas.

It's not about competition between the two divisions of data, Mr Rich is keen to note. When it comes to the "next evolution" of managing and governing data, it matters little which takes a lead role. This is perhaps a parochial way of thinking about it.

"Rather, the two related but distinct practices need to merge into a discipline called master data governance," he explains, citing Aaorn Zornes, chief research officer for the MDM Institute, as a key and insightful advocate of this view.

"Enterprise-level governance that spans both data and process is increasingly a key requirement put forth by IT executive management. While MDM purports to span the entire master data lifecycle – including creation, cleansing, harmonising and archiving – business process management claims to dominate the same for the business process lifecycle."

Mr Rich, who has been responsible for delivering data quality in areas such as product management and product marketing, concludes by saying that unifying the two areas requires overhauling technical and organisational challenges.