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Does “MDM” include data quality, data governance, and enrichment processes?

by Andrew White  |  February 4, 2010  |  6 Comments

I noted, with a wry smile, the following text in an Information Management article today, “MDM Achieving Maturity in Enterprises“,

“The findings of this report mirror our own client experiences, namely that there is an uplift in MDM adoption and an acceleration in delivery timeframes,” says  Jill Dyche, partner and co-founder of Baseline Consulting. “The fact that data quality, data governance, and data enrichment processes may accompany an MDM initiative make it all the more attractive as an enterprise solution.”

The part that made me smile was the implication that MDM could exist without data quality, data governance, and data enrichment processes.  Our view, and definition of MDM, always implied this.  How else could MDM (the discipline) be achieved?

Perhaps the comment is targeted more at “what is actually going on in the real world that is called MDM” in which case I can understand the point.  But, given the flurry of exchanges in the last 2 days, I thought this article’s timing was exemplarity (and perspective relevant).

Category: data-quality  governance  mdm  

Tags: data-governance  data-quality  mdm  

Andrew White
Research VP
8 years at Gartner
22 years IT industry

Andrew White is a research vice president and agenda manager for MDM and Analytics at Gartner. His main research focus is master data management (MDM) and the drill-down topic of creating the "single view of the product" using MDM of product data. He was co-chair… Read Full Bio

Thoughts on Does “MDM” include data quality, data governance, and enrichment processes?

  1. Jill Dyche says:

    Hi Andrew-

    As usual, your ear is to the ground. Thanks for the citation on your blog.

    You’d think you’d need data quality to do MDM right, wouldn’t you? The interesting fact is that MDM can indeed exist without data quality or data governance. We have several clients who are actually less mature in their data quality/correction/enrichment practices than they are with MDM. Why? Because they’re relying on the intelligence of a robust match engine to make the right data reconciliation choice. (Speaking of which, see Ode to Initiate on I have to be able to apply match processing against dirty data.

    If you look at D&B and Experian, they’ve learned to master data that comes to them ugly. The whole premise of MDM is to link disparate sources that represent information differently. And establish relationships between common values that are likely represented differently. Of course we recommend data cleansing. But the fact is that today’s clean data can be tomorrow’s dirty data. (My area code recently changed, for instance, which sucks for other reasons.)

    Likewise, we’ve seen MDM succeed without data governance. While I’ve said on multiple occasions that data governance is an MDM best practice, you can still establish relationships between common values that are represented differently without having a cross-functional data governance council in place. In fact I’d argue that most companies that are relatvively mature with MDM still have a ways to go with data governance. I’m sure you’ve seen the same.

    Thanks for the usual thoughtful blog post, and keep smilin’…

    Jill Dyche
    Baseline Consulting

  2. Andrew White says:

    Hi Jill,
    Thanks for your response.

    I suspect that our definitions of MDM may differ to some degree; and in fact your response highlights that difference. In fact your response makes a lot of sense, given the other dialogs I have had with others, recently, focused on aspects of MDM.

    I would not equate “matching” or “linking disparate sources that represent information differently” to MDM. I would equate those to “matching” and “linking”; both important aspects that would help achieve MDM. Gartner defined MDM (the discipline) as an IT enabled discipline oriented around maintaining “single view” of certain (master) data across the enterprise. Governance was explicitly included in the definition – but elsewhere we explore what we mean by governance.

    Governance does not have to be a large organization. For many organizations, governance is “Mike” – the guy that has been with the firm for 16 years and knows the place backwards. For some other organizations, governance is a virtual team of IT and business users that orchestrate and manage semi automated processes to preserve “single view”. Matching and linking are part of both of these – to varying degrees.

    So your point of view makes perfect sense, when I take into account a different definition of MDM. I think much of the differences in definition stems from the history of where the individual parts come from. Much CDI was oriented at transaction level harmonization (hence IBM’s “transaction” use case) that focused on matching and linking technologies. Much PIM was oriented to workflow and people processes (hence IBM’s “collaborative” use case), as well as text string parsing (mostly on the buy-side). The former did not need UI’s or complex/active governance infrastructures. The latter needed something along those lines. For some reason, a few folks (I don’t think you are in this bucket) forgot to check if product data was ever integrated in transactional systems; or if other important (master data) ever needed more than a 2 humans working together to create it. Hence for us, MDM is more holistic and inclusive of all of these pieces.

    Lastly I do agree with your point that all manner of implementations widely hugely. A lot that goes by the name, “MDM” isn’t, could be, might be, and sometimes is. I see lots of “data integration” efforts that lack governance, among other things, go by the name MDM. We try to show how this is not MDM; it is just another data integration effort. I guess all these differences gives us lots to talk about, right?

    Thanks again – good dialog. I hope my response makes sense.


  3. Jill Dyche says:

    Hi Andrew.

    Yup, Gartner’s definition of MDM differs from Baseline’s definition. What you guys call MDM we call “data management.” Like you, we have a formal definition of MDM (blah, blah, blah), but essentially we differentiate data management from mastering reference data. Absent the processing pieces–including matching and linking–MDM is simply a set of (necessary and rigorous) practices, which we see as data management. So merely having a list of reference values is data management; reconciling various formatting and value differences across different systems is MDM.

    Evan wrote a good blog post about this: where he explained that MDM is both “mastering data management” and “managing master data.”

    I’m sure it’s not the last construct or concept any of us will introduce on this topic. As it is, my brain is starting to hurt…


  4. Andrew White says:

    Hi Jill,

    Thanks again for the response. There were a few points I didn’t quite get. I saw:

    1) “What you guys call MDM we call “data management”.”
    2) “MDM is simply a set of (necessary and rigorous) practices, which we see as data management.”
    3) “So merely having a list of reference values is data management; reconciling various formatting and value differences across different systems is MDM”.

    I don’t know that Gartner has a term to describe “having a list of reference values”. What I do know is that the definition of MDM includes this capability, along with a lot of other things. So maybe I should interpret the points above differently:

    1) What we call MDM you call data management – for mater data only (I agree with that caveat)
    2) MDM is a subset of a broader thing called data management (I agree)
    3) Maintaining reference values is part of “data management”, and when managing references that represent mater data, its part of MDM

    I think this makes sense to me. Am I stretching too far?

    For reference, here is Gartner’s definition of MDM: “A technology-enabled discipline in which business and IT organizations work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official, shared master data assets.” Of course, the technology that goes by the name, MDM, may not do all this…

    I read the article you mentioned and found it interesting. We always included “management of master data” with “mastering/authoring of master data” in our MDM definition. So I agree: MDM is like “data management” (If I understand your definition) but only for master data.

    Have a good weekend.


  5. April Reeve says:

    I’ve been very surprised, like Jill, how the term “MDM” has recently been commonly used to include and assume many Data Management disciplines. This seems to be common with other Data Management terms as well: recently a client was using Data Governance to be a synonym for Data Quality and Data Management in general – all processes associated with Data.

    MDM in terms of system implementation might mean the implementation of central data stores such as Customer Master, Security Master, Reference Master, etc. However, without the associated processes of Data Governance and Data Quality the solution will likely not give the implementing organization their expected results. So, a matter or maturity of processes, I believe.

    Gartner’s definition of MDM sounds like a definition of Data Governance on Master Data, which I suppose is the literal definition of the term “Master Data Management”, so that makes sense.

    I expect, Andrew and Jill, you are both assuming that MDM includes Data Integration, without which central Master Data stores won’t get you very far, either.


  6. Andrew White says:


    Yes, I would agree that MDM includes a certain amount of “data integration” t help move data around the organizations. Just as I include in the definition of MDM the necessary governance of master data, and data quality of master data.

    Thanks for the post.

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