Data Quality: The Accuracy Dimension
An informative resource for any data management staff, IT management staff, and CIOs of companies with data assets.
TABLE OF CONTENTS Data Quality: The Accuracy Dimension
Chapter 13: Summary
The intention of this book is to promote the use of analytical techniques in pursuit of better accuracy of data in corporate databases. It has focused on the concept of accurate data and techniques that are particularly suited for finding inaccurate data. It outlines a complete process for formulating metadata rules and using them to efficiently evaluate data and to improve the completeness and accuracy of the metadata.
The book has several specific messages that together make a story. A summary of that story follows.
13.1 Data Quality Is a Major Issue for Corporations
| Note | Corporate databases are plagued with poor-quality data. The quality has become an ever-increasing problem. |
Can anyone doubt that this is true? The evidence is everywhere. The problem of poor data quality is pervasive, affecting all organizations with significant information systems activity. Corporate executives no longer deny data quality problems. Data quality is getting on more radars all the time.
| Note | The cost to corporations for poor data quality is high. Corporations generally do not know the cost. |
Quality improvement programs routinely disclose a sufficient number of issues to demonstrate the high cost of poor data quality. The number is always higher than anticipated. Day-to-day operational costs due to bad data are estimated as high as 20% of operating profit.
| Note | The cost of poor data quality is increasing. The quality of data is decreasing. |
As corporations get more complex through product line expansions, mergers, and acquisitions, requirements to comply with increasingly complex government regulations, and...
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