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Meta Data & Knowledge Management:
Meta Data Repository Myths

  Column published in DM Review Magazine
March 2002 Issue
  By David Marco

As the meta data repository industry continues to grow, so do the myths and misunderstandings surrounding this market segment. This month, I am going to address the most common meta data myths and set the record straight.

Myth 1: Meta Data Only Exists in Tools and is Only Used For Tool Interoperability. Before we dive into this myth, let's revisit the definition of meta data. Meta data is: All physical data (contained in software and other media) and knowledge (held by employees and various media) from within and outside an organization, containing information about a company's physical data, industry, technical processes and business processes."1

This definition of meta data can be pared down to one word: knowledge. Meta data electronically captures the knowledge, both technical and business, that exists in our companies.

When we review where knowledge exists within our companies, it is clear that the vast majority of knowledge is stored within the minds of the employees (see Figure 1).

Figure 1: Where is Corporate Knowledge Stored?

Clearly, meta data is much more than what exists in a tool. This misconception employs a limited view of technical meta data and completely ignores business meta data. Business meta data is every bit as important and often even more valuable. As IT professionals, we need to understand and learn how to capture, maintain and disseminate business meta data.

I don't want to create any misunderstandings; software tools store a great deal of very valuable meta data. Extract, transform and load (ETL) tools (e.g., Ascential, Informatica), data modeling tools (e.g., ERwin), relational databases (e.g., Oracle, DB2, MS SQL Server) and business intelligence tools (e.g., Business Objects, Cognos) all have very valuable technical meta data that is commonly stored in a repository.

A related misconception is the belief that meta data's only purpose is to enable software tools to communicate with one another (tool interoperability). In fact, meta data standards (e.g., Object Management Group's Common Warehouse Metamodel) often place significant focus on tool interoperability. Once again, tool interoperability is important; however, it is only one piece of the complete meta data management pie.

Myth 2: Repositories Always Require a Large IT Development Effort. This misperception is as common for data warehouse initiatives as it is for meta data repository projects. Far too often, corporations approach meta data repository initiatives from the standpoint of what they "can" capture as opposed to what they "should" capture. A company must decide upon the business and technical objectives they are looking to accomplish by building an enterprise meta data repository. Then, they should take a subset of these objectives and build the repository in an iterative manner to accomplish these objectives.

A good meta data repository is best built iteratively. Do not misunderstand; this is not to advise against building a fully functional, enterprise-wide meta data repository that supports all of a company's systems. It simply means that the highest probability for success comes from implementing a meta data repository in a phased approach. For our repository clients, I always look to target six- to nine-month project cycles. Using the first iteration as an opportunity to train the corporation will set the stage for bigger and better future implementations.

Myth 3: A Centralized Architecture Stores All Meta Data Centrally. There is a belief that when the term central meta data repository is used it means that all meta data should be stored centrally. This belief is the equivalent of believing that data warehouses should store all of a corporation's data. This impression couldn't be further from the truth. Only meta data that is necessary to meet the defined business requirements should be stored centrally. For example, business rules and business definitions are critical meta data that should obviously be stored in a centralized fashion. On the other hand, if there is no requirement to store specific meta data, it can remain in its current source.

Understanding these myths will help you build a successful meta data repository that provides your company with a competitive advantage.


1. Marco, David. Building and Managing the Meta Data Repository, John Wiley & Sons, 2000.


Check out DMReview.com's resource portals for additional related content, white papers, books and other resources.

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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