Columns

Editorial: Volume 1, number 1

• By Michael W. Bucken
• October 3, 2002

Welcome to the inaugural issue of Data Insight, a joint effort of the staffs of Application Development Trends and our sister group, TDWI. In this publication, we hope to provide some impartial insight into the value of data warehouse systems and the tools and technologies used to build, implement and maintain them. Perhaps most important in this day and age, we hope to shed some light on how such projects can be kept within tight budgets and cut long-term costs significantly.

In this issue, we'll take a look at data warehousing issues from a variety of perspectives of importance to ADT readers, TDWI members and to readers of our sister publication, Enterprise Systems. The content combines the expertise of the highly regarded Data Warehousing Institute with insight from the journalists and experts who regularly contribute to ADT.

Clearly, data and the straightforward access to it has become vital to corporations throughout the world. Technologies and data warehouse tool suppliers have come and gone over the past several years, but demand for viable warehouse solutions is as strong as ever. Executives, managers and workers alike need access to specific data to do their jobs.

Our lead story features the widely acknowledged know-how of Wayne Eckerson, director of education and research at TDWI, on the importance of data quality to a corporation's bottom line. Eckerson's story expands on a piece he contributed to the May issue of ADT, ''Data quality and the bottom line.''

Eckerson provides an in-depth description of a sound methodology for cleansing data and ensuring that data quality remains. Studies conducted by TDWI have found the cost of poor-quality data to be at least in the several hundreds of millions of dollars. The steps Eckerson describes aren't easy for any company to follow, but implementing a corporate data-quality method is critical because, as the author notes, dirty data can ultimately be the ruin of a company.

We also take a look at how corporate users are implementing different types of data warehouse systems , and sound out managers on the implementation process and whether the systems meet the initial promise of relatively easy access to high-quality data.

And finally, we've compiled a listing of tools and technologies for planning, building and implementing a corporate data warehouse. Regular contributors Lana Gates and Donna Sussman worked long hours to make the list as comprehensive and up-to-date as possible.

Related stories:
Delivering high-quality data by Wayne W. Eckerson
From the field: Data warehouse implementations by Rich Seeley, Jack Vaughan and Michael W. Bucken
Data Insight product guide compiled by Lana Gates and Donna Sussman