Ebook: Data Quality

Data Quality provides an exposé of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.

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Data Quality provides an expos? of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.

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Data Quality provides an expos? of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.
Content:
Front Matter....Pages i-xv
Introduction....Pages 1-17
Extending the Relational Model to Capture Data Quality Attributes....Pages 19-35
Extending the ER Model to Represent Data Quality Requirements....Pages 37-48
Automating Data Quality Judgment....Pages 49-62
Developing a Data Quality Algebra....Pages 63-77
The MIT Context Interchange Project....Pages 79-92
The European Union Data Warehouse Quality Project....Pages 93-117
The Purdue University Data Quality Project....Pages 119-137
Conclusion....Pages 139-147
Back Matter....Pages 149-167

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Data Quality provides an expos? of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.
Content:
Front Matter....Pages i-xv
Introduction....Pages 1-17
Extending the Relational Model to Capture Data Quality Attributes....Pages 19-35
Extending the ER Model to Represent Data Quality Requirements....Pages 37-48
Automating Data Quality Judgment....Pages 49-62
Developing a Data Quality Algebra....Pages 63-77
The MIT Context Interchange Project....Pages 79-92
The European Union Data Warehouse Quality Project....Pages 93-117
The Purdue University Data Quality Project....Pages 119-137
Conclusion....Pages 139-147
Back Matter....Pages 149-167
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