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  1. Introduction
  2. The Master Data Challenge
  3. Advantages of Master Data Management
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Advantages of Master Data Management

In an ideal world, all common master data in an organization would be stored and managed in a single place. The data would be accurate, consistent, and maintained in a coherent and secure manner. All updates would take place against this single copy of master data, and all of the various users of master data would interact with this single authoritative sourceof information. For customer data, such an arrangement means that all applications that use customer data would go to a single source; the data stored there would be the customer data used, for example, to open and close accounts across all lines of business, for statement provision, and for all marketing and analysis.

A single source of master data represents three important capabilities:

  • Authoritative source of information
  • Ability to use the information in a consistent way
  • Ability to evolve the master data and the management of the master data to accommodate changing business needs

A suite of services could be created around this master data, allowing the data to be integrated seamlessly into business processes and analytical environments. Together, these three capabilities provide organizations with a powerful foundation for efficient business execution.

An authoritative source of master data can be trusted to be a high-quality collection of data that follows a well-defined and agreed-upon structure. Clean data has been standardized (for instance, all address information follows the same format). Duplicates have been rationalized. The currency of the information is maintained through continuous or periodic updates. The information is complete, secure, and accurate.

Authoritative master data exposed through reusable business services provides the organization with the flexibility to exploit master data in new ways, by enabling applications to follow repeatable, defined patterns of usage in operating over this data. For instance, in a banking environment, customer profile information maintained as part of the master customer data can be used consistently across all of the various ways in which a customer may interact with the different parts of a business—branch teller, call center representative, and Web—to ensure a smooth and consistent customer experience. Each of the supporting systems would use the same business service to retrieve customer information. As new opportunities to interact with the customer arise—for example, via a customer's cell phone—again, the same services can be reused, because both the data and the method of use have been standardized.

A critical element in this ideal world of master data is flexibility. As business requirements, regulations, and implementation technologies change, we often find that the definition and use of the master data needs to evolve as well. In our ideal world, this type of change would not be a disruptive to the environment. For example, if a retailer decides to open stores in a new country, it should be easy to extend the definition of its products to accommodate additional information, such as new currencies and new regulatory requirements. At the same time, we don't want this simple data model change to break existing applications. Thus, the master data environment must support a smooth evolution of the data structures as well as the services that manage the behavior of the master data. In addition to supporting evolution, the ideal system supports the extension of the environment; for example, to add new domains of master data, and the linkages between them, in a nondisruptive manner.

The goal of master data management (MDM) is to enable this ideal world. Through a combination of architecture, technology, and business processes, MDM is an approach to reducing the amount of redundantly managed information incrementally, providing information consumers throughout an enterprise with authoritative master data. MDM systems that focus exclusively on managing information about customers are called customer data integration systems. MDM systems that focus exclusively on managing the descriptions of products are called product information management systems. MDM systems that enable multiple domains of master data, and that support multiple implementation styles and methods of use, sometimes are called multi-form MDM systems.

Book Preview

This article is an excerpt from the upcoming book: Enterprise Master Data Management: An SOA Approach to Managing Core Information, written by Allen Dreibelbis, Eberhard Hechler, Ivan Milman, Martin Oberhofer, Paul van Run and Dan Wolfson, published by IBM Press (ISBN-10: 0132366258, ISBN-13: 9780132366250). The book covers many of the key aspects for understanding what is meant by Master Data Management, the business value of Master Data Management, and how to architect an Enterprise Master Data Management Solution. The book describes the relationship between MDM and Service Oriented Architectures and the importance of data governance for managing master data. It also provides a comprehensive guide to architecting a Master Data Management Solution that includes a reference architecture, solution blueprints, architectural principles, patterns and properties of MDM Systems.

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