Rules Matter, Even For Data

  Business Intelligence   Strategy  

A writer once asked, "Why do we get wrong answers when we combine two operational databases that were both known to have perfectly adequate data quality prior to their joining?" The answers to this question are many and depend upon the situation at hand. However, one thing has become clear: The question is of critical importance to businesses.

Costly Consequences
Organizations are not only using more data-dependent applications, but they are also consolidating them to build enterprise systems. One consequence of this is that the quality of data has become more important.

A recent study by the Data Warehouse Institute found that poor data quality costs businesses $611 billion per year in the United States in printing, postage and staff overheads. It also estimates that 75 percent of businesses have experienced significant quality problems due to faulty data and that only 33 percent of businesses are confident of the quality of their data. The report concludes that the cost of poor data may be 10 to 25 percent of the total revenues of a company.

Most business applications are dependent upon data, and therein lies a problem. The quality of data degenerates quickly even when it is not touched or modified. Industry experts say that close to 2 percent of customer records become obsolete every month due to death, change in marital status, etc. Then there are other reasons …

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