This article originally appeared on the BeyeNETWORK.
For the longest time, data warehouses were justified by intuition. People just knew that they were the right thing to do. Then there were attempts to justify data
Then, one day, there appeared the practice of looking for the justification of a data warehouse by examining a corporation that had a data warehouse versus a corporation that did not have a data warehouse. In comparing these instances, it was seen that a data warehouse dropped the cost of information dramatically. The cost of building and maintaining the data warehouse was made insignificant by the cost required to gather and integrate information where there was no data warehouse.
In addition, when an organization had a data warehouse, the speed with which information was available was increased significantly. Even though it was hard to calculate, the time-value of information was greatly improved by a data warehouse. With a data warehouse, you simply can get analytical information much more quickly than if you do not have a data warehouse.
There has been over the years a lot of discussion about how to justify a data warehouse. And rightfully so. Corporations wish to know that the investment that they are about to make is going to return at least an equal amount of money.
The other day, I was in an organization’s headquarters, and I heard a really eloquent way of justifying a data warehouse.
A highly placed official at a multibillion-dollar organization stated to his staff: “We run our organization on spreadsheets. Finance has their spreadsheet. Engineering has their spreadsheet. Accounting has their spreadsheet. Marketing has their spreadsheet. And we don’t even know what the actual corporate numbers are. Everybody has their own spreadsheet, and no two people have data on their spreadsheet that is in any way related to the data on another person’s spreadsheet. So how do we make decisions around here? We make decisions based on popularity. John is a nice guy and does well at parties, so I think I like his data. Judy, on the other hand, is a gossip. So I don’t like her data. Is this any way to make decisions? We are making decisions of millions of dollars based on spreadsheets that may or may not have some basis in reality!”
And there you have it. A data warehouse gives a corporation a foundation of corporate numbers. Not accounting numbers about cash flow, but corporate numbers. Important numbers about:
- Sales calls and productivity
- New product
- Old products
These numbers are at the very heart of understanding the business of the corporation. Without a corporate set of numbers, we have a bunch of talented singers singing different songs. We have Aretha Franklin singing soul, the Eagles singing classic rock, the Thompson Twins singing grunge and Celine Dion singing pop. And in the background, we have Dave Brubeck doing jazz accompanied by the Steve Miller Band doing “Jet Airliner.”
The problem is that these artists are all doing it at once and it sounds just terrible. It is a bunch of noise coming from very talented singers. What we need is a little coordination among these talented artists. We need for them to be singing from the same songbook and from the same page in that songbook. When each of them sings or plays a different song and they do it all at once it just isn’t very pleasant. Nobody is pleased.
And that’s what a data warehouse does. That is the best way to understand the value that a data warehouse provides an organization.
And what about spreadsheets? Do they go away in the face of a data warehouse? Not at all. There are still plenty of spreadsheets. But the basis of the data found on the spreadsheets becomes the data warehouse. And once the data warehouse becomes the foundation for the spreadsheets, we now have a way to coordinate or at least relate and reconcile the data found on those spreadsheets. But without a data warehouse, we are lost.
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.