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Business Metadata – Whither Thou Goest?

Originally published September 14, 2006

 

Metadata is data about data – and it is just that simple. Or is it really? 

 

Take technical metadata. There are all kinds of metadata out there. There are code books, DBMS directories, field layouts and record layouts. There are data models. There are data flow diagrams and functional decompositions. These forms of metadata have been around forever (or at least since the early 1960s). 

Technical metadata is metadata that is useful to the technician and in the format and nomenclature of the technician. What exactly is technical metadata? Technical metadata is an abstraction of data. Table names describe how a table is to be accessed. Often, table names describe what is to be found in the table. Field or element names are a description of the contents of a field. Data flow diagrams describe work flow. Functional decompositions describe successively lower levels of processing, and so forth. In every case, technical metadata describes some aspect of the life of technology. 

Now let’s consider business metadata. Business metadata is metadata that is cast in the format and nomenclature of the businessperson. Business metadata is not designed for the technician. A simple example of business metadata might be the business definition of revenue (e.g., revenue is actual monies received either in cash, check or other fiduciary instrument). 

However, there are some problems with business metadata. The first problem of business metadata is that there is not the clean abstraction that can be found in the world of technical metadata. In technical metadata, there are these rather neat classifications of technology: table names, data elements names, data elements descriptions, data flow diagrams, data models and so forth. 

In the world of business, however, there is an almost infinite number of abstractions. In the world of business, practically everything is an abstraction of everything else. The term “women” describes half of the human race. The term “American” describes people who live in North America (more or less). The term “blue collar” describes a class of people who have common working habits and so forth. There are many, many different ways to classify and describe the same individual, all of which may be correct. One individual may fit into (literally!) hundreds of classifications. We do not have this dilemma in the world of technical metadata, or at least we do not have this dilemma to the same extent that we have it in the world of business metadata. And, for this reason, the world of business metadata is much more complex than the world of technical metadata. 

There are other complications as well. Another major difference between the world of business metadata and technical metadata is that of the location where metadata resides. After all is said and done, technical metadata is fairly well behaved. Technical metadata exists in very predictable locations. (All this, despite the moaning and complaints of the analyst who has to go gather and organize technical metadata!) 

Business metadata, on the other hand, can exist practically anywhere. Business metadata can exist on the Internet, on the front pages of the newspaper, in a library, in a tax form, in the Bible, in quarterly filings of a corporation, and so forth. This makes the job of the analyst who is trying to gather and assimilate business metadata infinitely much more difficult than the job of the person tangling with technical metadata. 

Having stated all of this, is business metadata worth the hassle? The answer is that if it is properly gathered, properly organized and properly presented to the end user, business metadata can be one of the most important information assets of the corporation.

  • Bill InmonBill Inmon

    Bill is universally recognized as the father of the data warehouse. He has more than 36 years of database technology management experience and data warehouse design expertise. He has published more than 40 books and 1,000 articles on data warehousing and data management, and his books have been translated into nine languages. He is known globally for his data warehouse development seminars and has been a keynote speaker for many major computing associations.

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