Many companies are focusing explicitly on identifying, extracting and loading data, and not enough on assessing their data quality, Gartner says.
Inadequate attention to data quality issues will result in more than half of data warehouse projects receiving limited acceptance or failing outright through 2007, according to a research firm.
Gartner Inc. plans to release findings indicating that many companies are focusing explicitly on identifying, extracting and loading data, and not enough on assessing their data quality. The conclusions are based on direct feedback from Gartner clients and a recently completed study of more than 900 companies from North America, Western Europe and the Pacific.
The chief pitfall for data warehouse projects is a lack of involvement by staff on the business side, Gartner said. IT-dominated data warehouse and BI initiatives often ignore business requirements, analyzing data that doesn't produce valuable business findings.
While IT-centric data warehouse projects tend to fail, those executed with the help of centralized, in-house BI "competency centers" are more likely to succeed. Such groups combine IT and business workers to steer data warehouse initiatives.
"You need ETL (extract, transform and load) and data warehouse expertise, but you also need analytical skills," said Howard Dresner, vice president and research fellow at Gartner. "And finally, you need some business people in there."
Gartner will release more BI-related findings at a summit the research firm holds in Chicago the week of March 7.
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