The Architecture for the Next Generation of Data Warehousing

Data warehousing has been around for about 2 decades now and has become an essential part of the information technology infrastructure. Data warehousing originally grew
in response to the corporate need for information—not data. A data warehouse is a construct that supplies integrated, granular, and historical data to the corporation.

But there is a problem with data warehousing. The problem is that there are many different renditions of what a data warehouse is today. There is the federated data warehouse.

There is the active data warehouse. There is the star schema data warehouse. There is the data mart data warehouse. In fact there are about as many renditions of the data warehouse as there are software and hardware vendors.

The problem is that there are many different renditions of what the proper structure of a data warehouse should look like. And each of these renditions is architecturally very different from the others. If you were to enter a room in which a proponent of the federated data warehouse was talking to a proponent of the active data warehouse, you would be hearing the same words, but these words would be meaning very different things.

Even though the words were the same, you would not be hearing meaningful communication. When two people from very different contexts are talking, even though they are using the same words, there is no assurance that they are understanding each other.

And thus it is with fi rst-generation data warehousing today.

Into this morass of confusion as to what a data warehouse is or is not comes DW 2.0.
DW 2.0 is a definition of the next generation of data warehousing. Unlike the term “ data warehouse, ” DW 2.0 has a crisp, well defined meaning. That meaning is identified and defined in this book.

There are many impotant architectural features of DW 2.0. These architectural features represent an advance in technology and architecture beyond first-generation data ware-houses.


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