Are data governance and MDM still inseparable?

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Yes. But since this post needs to be more than a one-word answer to its title, allow me to elaborate.

Data governance (DG) enters into the discussion of all enterprise information initiatives. Whether or not DG should be the opening salvo of these discussions is akin to asking whether the chicken or the egg came first. However, any initiative believing its manifest destiny is to expand across the organization and pervade every nook and cranny of the enterprise eventually needs DG. Master data management (MDM) is no exception.

One thing differentiating MDM is its focus on providing the organization with a single view of master data entities (parties, products, locations, assets). It does this by consolidating, standardizing and matching common data elements to achieve a more consistent view of these entities across the organization, creating their best data representations – often referred to as the organization’s single version of the truth. Another important aspect is the party-role relationship, which is where MDM manages the data and relationships underlying the high-level terminology commonly used in business discussions about the party master data entity (e.g., customer, supplier, employee). This complex challenge is perhaps best exemplified when the customer role crashes the MDM party.

As you might imagine, or may have painfully experienced, what MDM is attempting to accomplish involves much more than data and technology. For example, even as a concept MDM’s single version of the truth must contend with the various versions of verisimilitude believed by people across the enterprise. And as an implementation, MDM must consider the lesson learned by many an enterprise data warehouse past (and possibly present): Just because you beautifully build it doesn’t mean people will dutifully use it.

People, and the unique corporate culture they embody, can make or break MDM. This is where DG comes in. DG provides the guiding principles and context-specific policies that frame the processes and procedures of MDM.

1421435697166[1]An example of a DG guiding principle for MDM is “master data will be managed as a shared asset to maximize business value and reduce risk.” DG policies for MDM will provide context to the specific business uses of master data, such as the different ways billing and marketing define who a customer is, and who has the authority to access sensitive data (e.g., social security and credit card numbers) describing those customers. DG will connect the dots between these principles and policies and MDM processes and procedures, making sure principles are followed, policies are enforced, and any and all changes are well-communicated across the organization.

While it is possible, and definitely easier, to start MDM without DG, MDM isn’t done until it invites DG to the party (and to the product, location and asset too). This is why DG and MDM still are, and forever will be, inseparable.

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Jim Harris

Blogger-in-Chief at Obsessive-Compulsive Data Quality (OCDQ)

Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.

2 Comments

  1. Unless data quality, governance and seamless integration of operational/transactional data with master data is addressed UPFRONT and semantic meaning assigned, in real-time, then meaningful customer-centric analytics/CRM/BPM will never bring the maximum business value.

  2. Thanks for sharing such an informative post on data governance and MDM. Profoundly described the data governance functionality and its increasing need in estbalished enterprises. Nice Share!

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