http://www.mksinc.com/datawarehouse.htm TO READ MORE

Data Warehousing and Knowledge Discovery Technology

Data Utilization for Dollars and Sense

News & Views Feature Article

by John Thomstatter

MKS, Inc.

Originally published in News & Views September, 1997 issue.

Copyright 1997 STC-Philadelphia Metro Chapter. For permission to reprint this article, contact the Managing Editor.

Rapid changes in information technology have dramatically increased our ability to generate, collect, and store data. The widespread use of corporate business software and data collection hardware, such as scanners and bar code equipment, continues to increase our ability to accumulate huge amounts of data. Increased capacity and reduced cost of storage devices further encourages the retention and storage of this data. Explosive growth in the collection and storage of data has led to the expansion of other facets of the information industry--Knowledge Discovery in Databases (KDD) and Data Warehousing. The intent of KDD, or Data Mining, another commonly used term, is to extract knowledge from historical data for strategic analysis and business planning.

Data Warehouse is the term used to describe "a copy of transaction data specifically structured for query and analysis."(Kimball, 1996) An article in the July issue of the DIGITAL Today newsletter estimates the Data Warehousing market at $8B annually with a 47% annual growth rate.("Targeting" 1997) This creates another opportunity for technical communicators to document the features, capabilities and use of the technology. Data Warehousing and KDD, like artificial intelligence (AI) technology, are not "plug and play" software solutions.

The elements of the knowledge discovery process include: the online transaction data which is restructured into a Data Warehouse format; a Decision Support Software (DSS) tool which is used to define the data access and rules for analysis, as well as extracting and interpolating the data; and a PC spreadsheet or similar software package which receives the DSS results and further manipulates or formats the data into a decision statement.

Data modeling and data warehouse