Meta Data and Data Administration:
Meta Data Architecture Fundamentals
Over the next few years many companies will have the unenviable task of completely rebuilding their decision support systems. This is occurring because many of these systems were built with flawed architectures. The architecture used to build the meta data repository is every bit as critical to its long- term viability as the architecture for the decision support system is. By taking the time to build a sound architecture, your repository effort will be able to grow and mature over time to support all of your company's meta data needs.
A meta data repository is the logical place for uniformly retaining and managing corporate knowledge within or across different organizations within a company. Over the past several years, a number of meta data repository architectures have emerged to address the challenges for administering and sharing meta data within an enterprise. The two most common approaches to building a meta data repository architecture are centralized and decentralized.
For most small- to medium-sized organizations, a single meta data repository (the centralized approach) is sufficient for handling all of the meta data required by the various groups in the corporation. This architecture, in turn, offers a single and centralized approach to administering and sharing meta data. On the other hand, most large enterprises that have multiple and disparate divisions will require several meta data repositories (decentralized approach) for handling all of the corporation's various types of meta data content and applications.
This approach is the most common one that corporations have implemented. The key concept of a centralized meta data architecture (see Figure 1) is a uniform and consistent meta model that mandates the schema for defining and organizing the various meta data stored in a global meta data repository. The strength of this approach is that it integrates all of the meta data and stores it in one meta model schema that can be easily accessed.
Figure 1: Centralized Meta Data Architecture
A decentralized meta data architecture creates a uniform and consistent meta model that mandates the schema for defining and organizing the various meta data to be stored in a global meta data repository and in the shared meta data elements that appear in the local meta data repositories (see Figure 2). All meta data that is shared and reused among the various repositories must first go through the central global repository, but sharing and access to the local meta data is independent of the central repository.
Figure 2: Decentralized Meta Data Architecture
While this architecture provides the means for centrally managing the administration and sharing of meta data across multiple meta data repositories, it also allows each local repository to be autonomous for its own content and administration requirements. This architecture is similar to a federated management in that its central governing architecture provides the guidelines that are common to all of its members, and each of its members can also create localized guidelines for their specific needs.
Both of these approaches have their advantages and disadvantages. Choose wisely and your repository will support your company's requirements for many years to come.
For more information on related topics visit the following related portals...
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David Marco is an internationally recognized expert in the fields of enterprise architecture, data warehousing and business intelligence and is the world's foremost authority on meta data. He is the author of Universal Meta Data Models (Wiley, 2004) and Building and Managing the Meta Data Repository: A Full Life-Cycle Guide (Wiley, 2000). Marco has taught at the University of Chicago and DePaul University, and in 2004 he was selected to the prestigious Crain's Chicago Business "Top 40 Under 40." He is the founder and president of Enterprise Warehousing Solutions, Inc., a GSA schedule and Chicago-headquartered strategic partner and systems integrator dedicated to providing companies and large government agencies with best-in-class business intelligence solutions using data warehousing and meta data repository technologies. He may be reached at (866) EWS-1100 or via e-mail at DMarco@EWSolutions.com.
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