Meta data often gets treated like Wednesday's child. It is an afterthought. It is extra baggage. It is documentation.

There are 100 reasons why meta data gets no respect, but it shouldn't be that way at all. In order to impress upon people the power and importance of meta data, I do this little exercise. I tell people, "I am going to give you some valuable information." I then write the number 4 on the board and say, "There it is."

They look at me blankly and say, "So what? That's not valuable information."


I then ask, "You want to know what that number means?"

I then put a dollar sign in front of the 4. Money always gets people's attention. Then I put U.S. in front of the $, indicating that the measurement is in U.S. dollars. People are now starting to get interested. Then I write the word "Oracle" beside the number. Even more people wake up now. Then I write "NASDAQ 2003."

Next I write, "A leading stock analyst predicted that Oracle stock on the NASDAQ exchange will rise at least $4 in 2003." Now everybody is interested.

Why is it that suddenly they are interested, but when I merely wrote the number 4 on the board they were bored silly? They made sense of what was being said through the addition of contextual information. And what is contextual information? Meta data.

Meta data gives us the context to make sense of what are otherwise random and arbitrary pieces of information. Meta data makes sense out of everything else. So why can't meta data get any respect?

The previous example helps the uninitiated to grasp the concept of meta data. Another way that meta data begins to make sense is through the explanation of what is needed in order to make sense of information over time. Consider the following (very normal) example.

One day a manager asks his analyst staff to produce a report covering the revenues of the corporation for 1999. Because they have a data warehouse and the historical information has been captured at the detailed level, the staff generates the report very quickly. The manager is told that there was $40 million in revenue in 1999. Because the staff was so efficient, the manager requests a report for the year 2000. The staff reports that in 2000 the revenues were $25 million. The manager looks at the two reports in disbelief. How could it be that there was a drop of $15 million in revenue in one year? The manager says, "You guys in analysis are simply not to be believed. This just didn't happen."

Before the analysts take it lying down, one analyst steps forward and explains.

"Do you recall that in 1999 we included Mexico and Canada revenues as part of the total? In 2000 we made the executive decision not to include them. And do you remember that in 1999 there was a very favorable exchange rate, but in 2000 there was a terrible exchange rate? And do you recall that in 1999 FASB had one set of rules for revenue recognition, but in 2000 there was another set of rules for revenue recognition? Do you recall that in 2000 we sold off a major portion of our business? When you take into consideration all of these things, it is a wonder that revenue did not drop any further."

The manager who requested the reports now says, "Oh, yeah. I remember all of that. Now I can make sense of comparing numbers from one year to the next."

Where did much of the information that was used to describe the information over time originate? It came from the context supplied by meta data. Looking at data from one point in time makes sense compared to other points in time only when there is meta data that explains what the data means.

The next time someone disrespects meta data, chalk it up to their inexperience. It may be true that meta data gets no respect, but it sure ought to. Part of maturing in the information profession involves coming to grips with the importance of the entire information infrastructure, of which meta data is a significant part..

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