The most important data model in the enterprise is the meta data model.
Author's Note: This column is adapted from the book Universal Meta Data Models by David Marco and Michael Jennings (John Wiley & Sons).
Several years ago, I wrote an article about a generic meta data repository model for use in the business intelligence environment. This model was different because it attempted to illustrate an area of the data warehouse environment seldom focused on at the time. It highlighted the central area of all processing in the business intelligence environment, but it was limited in its scope. The generic meta data repository model focused solely on the meta data, the context of the content, of the data warehouse. While this was an important area, it neglected the other areas of meta data collection and usage throughout the entire enterprise. The complete meta data model attempts to go beyond the earlier meta data model by providing a more holistic view of the entire enterprise environment. Like the generic meta model, the complete meta data model is not only useful for a specific business function or vertical industry; it can be utilized across any type of business because the model's purpose is to capture and store meta data (data about data).
This is the first installment of a seven-part series on the purpose, detail and usage of the complete meta data model managed meta data environment (MME). This installment begins the series with a general discussion of the purpose and components comprising the complete meta data model. Subsequent columns will examine the various component areas that encompass the elements of the model. Each of these component areas will be examined in detail by focusing on and illustrating their particular modeling detail including their major interaction relationships with other model components.
The Complete Meta Data Model Components
Figure 1 illustrates the logical view of the complete meta data model. The model allows for meta data capture and storage about customer relationship management (CRM), enterprise resource planning (ERP), data warehousing, supply chain, operational systems, desktop applications, documents, spreadsheets, corporate Web site, e-business, enterprise application integration (EAI), Web services, extensible markup language (XML), software tools, organizational policies, business partners, vendors, customers, IT staff and a variety of other data management/business applications. The model depicts a logical view, not a physical implementation viewpoint. There are four component areas represented in the complete meta data model: enterprise systems; IT portfolio management; XML, messaging and business transactions; and business rules, business meta data and data stewards (see the legend in Figure 1). Each of these component areas will be explored in detail in subsequent parts of this series.
Figure 1: The Complete Meta Data Model
The data management sections of the model are represented by the enterprise systems component area. The purpose of the enterprise systems component is to define all of the data structures in the enterprise environment and describe the interrelationship of the associated meta data. This component is the base for all other model component areas. It is used to control and manage both data and meta data throughout the model. The enterprise systems component provides details into data, relationships, and the data movement and integration processes. The component is the reference source for system semantics and data structures in the model.
The management of an organization's IT assets is represented by the IT portfolio management component area of the model. These assets include areas such as service management, software management, hardware and network management, project portfolio management and data quality management. The IT portfolio management component area supports IT management as a business function of the enterprise. The objects of the IT portfolio management component represent real business items of the enterprise but are integrated with the management of standard categories of meta data (e.g., databases, tables, flat files, etc.). The IT portfolio objects are planned and managed together with these more recognizable meta data objects.
The next component of the model represents the meta data associated with XML due to its increasing pervasiveness throughout the enterprise. Today, most applications in the enterprise interact with XML at least at some level. These interaction levels include areas such as XML schemas (XSD), DTDs, XML transformations (XSLT), business transactions and classification schemes. XML documents are used in the enterprise for processing such as data transport between applications and Web services. The meta data used in conjunction with XML must be defined and used efficiently in order to avoid redundancy in the enterprise.
The relationship of the business to information is represented through the business rules, business meta data and data stewards component area. The purpose of this component is to support the business user view of the meta data. The meta data represented in this component imitates the way the user interprets and uses this information. This component provides a standard method for documenting, maintaining and approving the rules, definitions and people that run an organization. The data stewards of the organization are depicted because they characterize the meta data needed for the business to make decisions. This business meta data allows users to organize data according to the way the business sees the information. The business relationships of data can be understood regardless of the physical structures or technology used.
In the next installment of this series, we will take a closer look at the packages that comprise the complete meta data model.
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