MDM Foundations: Adding data governance to get to MDM


In my previous post, I outlined the main components needed for a phased approach to MDM. Now, let's talk about some of the other issues around approaching MDM: data governance and the move to enterprise MDM.

Where does governance come in?

Throughout your MDM program, it's important that deep expertise and rigor go into the planning phase, whether from within your organization or without. The SAS Data Management Consulting organization provides deep data governance and MDM planning expertise, which helps you minimize project risk and align IT initiatives with business objectives through targeted MDM or data governance engagements.

The business data glossary and reference data management components of our SAS Data Governance offering can help to ensure that business terms (like patron) and related attributes (like address, loyalty card level, and name) are related to technical metadata, which provides the specific tables or fields where this data resides. By providing a way to manage business terms and reference data, SAS Data Governance can be used to align business and IT.

For example, if you're trying to create a master entity for patron, business users can leverage the web-based user interface to define the patron entity attributes before exporting this information into MDM Foundations. MDM Foundations then provides for profiling and feeding cleansed data in batch for a single entity (like patron as well as customer, product, etc.) at departmental volumes. Entity matching rules (grouping by address, Social Security number and name attributes) can be visually created and experimented with using this "data quality sandbox," compressing the iterative data exploration cycle.

Stepping up to Enterprise MDM

When the organization requires real-time SOA access, higher volume, enterprise multi-domain MDM (single view of both product and customer, for example), relationship management across those domains, and server-based deployment for performance and centralized access, you can move up to the SAS MDM solution. And you can build on an existing data management platform.

No other MDM vendor can provide this phased approach to delivering business value. MDM solutions often don’t have embedded data quality and therefore rely on integration with products from other companies, sometimes recently acquired, to provide this essential benefit. It’s also much more challenging to find a professional services resource that is knowledgeable of multiple solutions since they often came from the recent acquisition of several different companies.

What if you already have an existing MDM footprint? SAS Data Quality can provide cleansing and standardization that is embedded as part of a real-time web service from operational system feeds or as a batch process when creating a staging file for import into an existing MDM solution. This may also be an opportunity to look at data quality vendor consolidation. Chances are you are using multiple data quality vendors throughout your organization for everything from address standardization and verification to data profiling to CASS certification. Why not consolidate into one unified user interface that can also be leveraged as the underpinning of your MDM solution? The same skills your data quality developers build can be leveraged to create or extend the MDM load jobs for the hub.

Wherever you are in the process, SAS Data Management solutions can help accelerate your time to value, reduce risk, and deliver value to the business with success at every stage.


About Author

Matthew Magne

Principal Product Marketing Manager

@bigdatamagnet - Matthew is a TEDx speaker, musician, and Catan player. He is currently the Global Product Marketing Manager for SAS Data Management focusing on Big Data, Master Data Management, Data Quality, Data Integration and Data Governance. Previously, Matthew was an Information Management Solutions Architect at SAS, worked as a Certified Data Management Consulting IT Professional at IBM, and is a recovering software engineer and entrepreneur. Mr. Magne received his BS, cum laude, in Computer Engineering at Boston University, has done graduate work in Object Oriented Development and completed his MBA at UNCW.


  1. MDM is about an Enterprise approach I assume.
    In that approach you also need some governance of standard of good practice

    What if the approach is abandoning the enterprise and is going for the most detailed subproces of some departmental work. What is the need for MDM in that situation?

    • Matthew Magne

      Hi Jaap,
      Thanks for your comment. If you are not spanning source systems of data or multiple applications, you don't need MDM. You just need to fix that application or source system. Often, even at the departmental level, you have differing views of data from multiple sources or applications and this is where MDM would come in.
      Hope that helps,

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