Informed CIO: MDM
Know Thy Data: The Power Of Master Data Management
With excellence in the use of information a key factor in business success, it is imperative for organizations to overcome information management and integration challenges presented by distributed data—or risk falling behind. Inaccurate or inconsistent data is often the root cause of higher business costs. Data problems lead to mistakes in how organizations handle customers, report financial results and build business processes that cross multiple applications. Strategic and operational decision-making get bogged down due to lack of confidence in the data. Organizations may fall prey to security, privacy and regulatory pitfalls because they cannot keep track of how data is being used.
Master data management (MDM) is a process that leading organizations are employing to improve knowledge about their data resources and to address data quality, consistency and related information management problems that arise, particularly as users try to access multiple sources. MDM focuses on gathering data about entities such as “customer,” “patient,” “product” and “policy” that business users define, usually without coordinating them across the enterprise. MDM can address this problem by building information integration models at a higher level. With greater abstraction, business users can benefit from integrated data without having to know, at a technical level, how to access the data and find their way through lower-level database structures.
MDM can help organizations discover and document how data in one system relates to data in other systems. Knowing more about such relationships is an important foundation for business analysis and modeling. It also helps organizations eliminate data redundancy and errors. That increased understanding is critical for data governance, an initiative organizations are undertaking to set policies and establish processes for sustaining data quality and consistency. Motivating data governance is concern about regulatory compliance.
MDM and master data are not always clearly defined. Common understanding of MDM can be elusive because processes can be specialized for particular domains, such as product information management (PIM) and customer data integration (CDI). MDM also splits into operational and analytic implementations. Finally, since organizations employ MDM to bring data quality, profiling, mapping and other steps into formalized processes, how they define MDM often depends on which steps they include. However, there is momentum among vendors and users to establish an all-inclusive, “multi-domain” approach to MDM, in part to preventing MDM systems from becoming simply more islands of information.