If bad data is put into a data warehouse, companies risk what Tony Fisher, president and general manager at DataFlux, described as “code, load and explode.””If the data from a source system doesn’t meet the expected qualities for that data, the loading process may fail, causing the company to stop the load process and try again,” Fisher said, which leads to implementations that exceed time schedules and budgets.DataFlux, based in Cary, N.C., provides data profiling, data quality and data integration technology to help companies inspect, correct and merge data prior to loading it into a data warehouse. Therefore, users can locate and resolve errors, helping improve the overall quality of data within the entire data warehouse system at a firm.”Each year, a large number of data warehousing initiatives fail because of erroneous or incomplete data,” Fisher said. “Inaccurate or incomplete data can lead to faulty decisions once the data warehouse is polluted with bad data.”This bad data costs companies billions. The Data Warehousing Institute, which provides research and business intelligence for the data warehousing industry, estimated that data quality problems cost U.S. businesses over US$600 billion a year.Rene Marcotte, a senior architect at Collaborative Consulting in Woburn, Mass., told CRM… Read full this story
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