The Metadata Repository : The Key to Knowledge Management
By David Marco

The following is an extract from one of many articles written by David Marco. He is an internationally recognized expert in the fields of enterprise architecture, data warehousing and business intelligence and is one of the world's foremost authority on meta data. He is the author of several books including, Universal Meta Data Models (Wiley, 2004) and the widely acclaimed book 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 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 via e-mail at

Benjamin Franklin once said: ''An investment in knowledge pays the best interest.'' Something tells me Ben didn't have knowledge management on his mind, but he was a pretty smart guy, so maybe he did. And today, corporations are beginning to understand what Franklin knew all those years ago: Knowledge is your most valuable asset.

Much of this push for knowledge comes directly from senior executives. In a survey of Fortune 1000 executives, 97% of respondents said some critical business processes would improve if more employees knew about them. In the same report, 87% of those surveyed said costly mistakes occur because employees do not have the right knowledge at the right time.

This tremendous desire to improve and maintain an organization's intellectual capital has triggered a field of study and class of vendor applications that we refer to as knowledge management, or KM.

When I first learned about KM, my immediate reaction was that the objectives of knowledge management seemed a lot like those of a meta data repository. Moreover, I don't see how a ''true'' enterprise-wide knowledge management solution can exist without a meta data repository. In fact, a meta data repository is the backbone of a knowledge management solution.

A meta data repository implements a technical solution that gathers, retains and disseminates corporate ''knowledge'' to generate a competitive advantage in the market. This intellectual capital (data, information and knowledge) is both technical and business-related.

Knowledge management benefits a corporation by leveraging ''lessons learned'' so users can share information to generate new ideas, increase revenue or decrease expenses; and by improving the firm's ability to adapt to change and opportunities in the market.

Knowledge pyramid

The knowledge pyramid is at the heart of knowledge management. Businesses are beginning to realize that to attain a competitive advantage they need their IT systems to manage more than just data, they need them to manage knowledge (meta data). As a corporation's IT systems mature, they progress from collecting and managing data, to collecting and managing knowledge.


Data is the basic building block of IT systems -- it is the transactional, physical record of an enterprise's activity, and organizations go to great lengths to capture and manage it. Data is captured each time a customer calls a business to place an order, including, at a minimum, the customer's name and address, the products ordered, any applicable discounts or sales tax, and the dollar amount of the order. Unfortunately, this data does not tell us why the customer purchased the product from this firm rather than a competitor, or how much they were willing to pay, nor does it predict whether the customer is likely to return. In addition, these data facts do not tell us if the organization is successful or if it is managed efficiently.


Data by itself has little purpose or meaning. Information is data that has meaning and purpose. In Working Knowledge: How Organizations Manage What They Know (Boston: Harvard Business School Press, 1998), Thomas Davenport and Laurence Prusak state that we add value to data in the following ways:

  • Contextualizing -- tells us the purpose for which the data was gathered;
  • Categorizing -- tells us the units of analysis or key components of the data;
  • Calculating -- tells us if the data was analyzed mathematically or statistically;
  • Correcting -- tells us if errors have been removed from the data; and
  • Condensing -- tells us if the data was summarized in a more concise form.

While this might seem a little ''big brained'' for us technicians, it relates to the process of making data have direct meaning to our business.

For example, by summarizing customer sales amounts and subtracting the expenses for serving that customer, we attain profitability numbers. If we do this for each customer, we can see which customers are the most profitable. In this way, we are able to turn data into information.

Knowledge. Knowledge is not an easy term to define. Epistemologists spend their entire lives trying to understand what it is to know something. For our purposes, knowledge takes information one step further than data. I think of information as data that tells me about my business and how it functions. When I go that extra step to transform information into knowledge, I understand how my business impacts the market in which I compete, how my business interacts with the other firms in the same selling space, and how my firm is influenced by the market in which we compete. So knowledge is how my business relates to the overall, global picture.

Interestingly enough, most magazines that discuss knowledge management fail to mention a meta data repository. I believe this glaring oversight exists because most knowledge management professionals focus on the business portion of the KM equation. However, as implementers we realize that a meta data repository is the technical solution for knowledge management.