It is trite to observe that data is a critical asset in the information age. Data is the "facts and figures" associated with customers, products and services, market and financial performance - indeed, every aspect of life in the information age. It is used to conduct every operation, no matter how mundane, and it is a crucial input to decision making and planning. Further, the sheer quantity of data acquired and stored by companies and government agencies is growing by leaps and bounds. The following quote of Lou Gerstner illustrates the point: "Inside IBM, we talk about 10 times more connected people, 100 times more network speed, 1,000 times more devices and a million times more data."1 Additionally, increasingly more data is published on the Internet as heretofore proprietary databases are made available to the public. There is no end in sight to any of these trends.

It is becoming increasing clear that much (probably most) data is of poor quality. Some data is simply incorrect, other data is poorly defined and not understood by data customers; still other data is not relevant to the task at hand. The impact is enormous. Poor quality data is at the root of many issues of national and international importance that dominate the news for weeks at a time. Fortunately of course, most data quality issues are more mundane. However, in aggregate, they may be even more costly.

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