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What's the relationship between master data management, data warehousing and service-oriented architectures?

Q: Are there any tradeoffs between stability versus flexibility during data warehouse design? Is there any documentation that shows this? Another question: I wonder now how master data management fits in an SOA implementation and in data warehousing? What's the relation between these three technologies?

Evan Levy's Answer: Here are a few quick and dirty definitions related to your questions that I'll use to support answering your question (please refer to the Web or Wikipedia to get a more thorough set of definitions:

  • Master data management (MDM) is the collection of processes, controls, automation and skills necessary to standardize and integrate a single subject data originating from different sources.
  • SOA is an architecture and interface to support the delivery of the results of application services and/or data services to other applications without burdening developers (or the calling application) with network navigation, data formatting, connectivity logic and other complexities traditionally associated with application-to-application or system-to-system connectivity.
  • A data warehouse is a system that supports and stores a company's cross-functional data. A data warehouse typically includes multiple subject areas.

How do they relate and work together?

Many MDM products have chosen to support SOA as a means of interfacing to applications. SOA is a more robust interface than traditional APIs and even SQL and simplifies the effort necessary to enable application access to an MDM server.

Because an MDM server can have data quality, cleansing and reconciliation built in, it provides a good way to improve data quality on a data warehouse as well as simplifying ETL processing for loading reference data onto a data warehouse. It's important to remember that MDM is typically focused on a single subject area and provides a solution for integrating data from multiple operational systems

SOA can be used as a means of interfacing to a data warehouse (although you wouldn't normally use SOA as a means of querying tables and columns). SQL is a data-oriented, set-based language that requires the user (or application) to understand data objects (columns, tables), domain values (are the columns char, numeric, etc.) as well as system access and navigation details. SOA is an interface that provides abstraction layer that hides the complexity of database tables, columns, data types and the like from the programmer. In order to support an SOA interface, the data warehouse would have to have server-based code that could convert the SOA-based requests into database-related requests.


Evan Levy is a partner and co-founder of Baseline Consulting Group, a multivendor systems integration and consulting firm. As the partner in charge of Baseline’s largest practice, Levy leads both executives and practitioners in delivering technology solutions that help business users make better decisions. He has led strategic technology implementations at commercial and public sector organizations and advises vendors on their product development and delivery strategies. Levy has been published in a wide array of industry magazines and has lectured on a range of technology delivery experiences at leading conferences and vendor events. He has been a featured speaker at the Marcus Evans Analytical CRM symposium, DCI’s Data Warehousing conference, the CRM Association, DAMA International, the AMA and the Data Warehousing Institute. His current work involves delivering and lecturing extensively on the topic of data integration. You can contact him at evanlevy@baseline-consulting.com.

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