Amazing Books
Temporary Blank

Monday, April 2, 2012

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.

Keywords : Data warehouse - Wikipedia, the free encyclopedia. Data Warehousing Concepts, data warehouse concepts, enterprise data warehouse, data warehouse architecture, data warehouse tools, data warehouse institute, what is a data warehouse, data warehouses, data warehouse certification, data warehouse consulting, kimball data warehouse, data warehouse products, data warehouse design, data warehouse architect, data warehouse solution, data warehouse vendors, management data warehouse, ods data warehouse, open source data warehouse, data warehouse tutorial, federated data warehouse, data warehouse companies, data warehouse consultant, software data warehouse, data warehouse applications, data warehouse systems, data warehouse reporting, data warehouse tool, cognos data warehouse, data warehouse interview questions, etl data warehouse, sql server data warehouse, shared data warehouse, data warehouse basics, data warehouse training, what is data warehouse, data warehouse manager, data warehouse application, data warehouse example, data warehouse software, healthcare data warehouse, data warehouse diagram, sql data warehouse, data warehouse etl, the data warehouse toolkit, data warehouse and data mining, data warehouse vendor, data warehouse testing, data warehouse specialist, bi data warehouse, data warehouseing

Data Warehousing Design and Advanced Engineering Applications Other Data Warehouse books

No comments:

Post a Comment

Related Posts with Thumbnails
There was an error in this gadget

Put Your Ads Here!
There was an error in this gadget