Quality is the theme of this book, which is directed primarily to practitioners who must maintain the integrity and secrecy of data in large databases. The topic, integrity of data, is unique in book form and is or should be of interest to data managers and to academic computer scientists and information system specialists. A survey of most work in the area is provided; an executive-style tutorial on some of the more technical topics is given.

Definition of data and the dimensions that must be considered if quality of data is to be maintained within a production environment introduce this book. Models of quality control follow with enough detail that both technical and managerial strategies for the establishment of quality of data can be understood by those not familiar with the approaches. Measurement systems and data quality aspects of current process design using simulation studies and experimentation are surveyed. The author indicates that many of the methods discussed have been developed by members of the Information Quality Group at AT&T Bell Laboratories in Holmdel, New Jersey. The level of detail is adequate for management to understand the problem and potential solutions and to allow management to lead in these efforts. The coverage is inadequate for this book to be used as an implementation guide for a comprehensive data quality program, however.

The author’s perspective on the need for significant improvements in the quality of data used in today’s world is insightful and forward-looking compared with current thought in most business and industry. The thesis that the quality of data must be addressed by a synthesis of managerial and technical methods is probably correct. His analysis that data quality should be a topic of serious research and of far greater concern for data administrators in business, industry, and institutions than it is currently is valid. The book is easy to read and ought to be required reading for database administrators.