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Data Errors Can Overturn Data Integration

By SiliconIndia   |   Thursday, 21 June 2012, 09:17 Hrs
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Bangalore: Data integration is a crucial step in Business Intelligence (BI) processes. This consists of pulling together data from multiple sources and then consolidating it in data warehouses for analysis. Data Management analysts warn that a BI Integration strategy can go askew if there is a fault in design or execution. This could derail your BI plans, as Alan R. Earls reports on

Claudia Imhoff, the President and Founder of Intelligent Solutions stated that bad timing could ruin everything: the loading of data into a data warehouse in time to be used for the planned BI purposes is crucial. There should be proper understanding of the organization’s BI requirements. According to Imhoff, good data quality is just as important. Correcting and cleaning up incorrect data shouldn’t solely rest on the BI data integration process. “Errors are happening everywhere else along the way, so you need to figure out where they are coming from,” she said. Then one must work to prevent data mistakes from finding their way into source systems in the first place.

Ted Friedman, an analyst at Gartner opines that not paying enough attention to data quality is the biggest BI data integration menace companies face. “I’ve been following data integration for more than 10 years and I still spend days talking to organizations that are not getting the usage and trust and acceptance and value out of their BI efforts because the quality of the data is not good enough, and they haven’t done the right things to fix that, “he said.

Barry Devlin, one of the founders of data warehousing, thinks the fundamental mistake is not including the right people in the process of designing a BI data integration strategy. “The people who really understand data and what it means are a particular subset of the business community who have been playing with data over the years -- they are the gurus and the power users,” Devlin said. As a result they’re best equipped to define what data needs to be integrated in order to create effective BI applications.

Sadly in most cases, it rests on the IT department to develop the data integration plan in addition to doing the implementation work. This coupled with an unrealistic schedule can derail a BI project. Any project team must remember to adequately scope the data integration requirements of a BI project in advance.

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