Springer Science & Business Media, 2001 - Business & Economics - 167 pages
Data Quality provides an exposť 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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Best case when error distribution is nonuniform
The MIT Context Interchange Project 79
Summary and Conclusions
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accuracy aggregation algebra algorithm analysis application quality requirements approach Autoclass Ballou base relations Cartesian product Chapter comparison vectors components Computer conceptual Conference on Information Context Interchange corresponding D. P. and H. L. data consumers data integration data model data quality dimensions Data Quality Management Data Quality Measure data quality metrics data quality reasoner data quality requirements data warehouse data warehousing Database Systems decision tree defined denote DEPT1_EMP developed dominance relationships example Figure gerund H. L. Pazer heterogeneous identified information manufacturing system Information Quality information sources Information Systems International Conference linking logical mediation meta-modeling methodology OLAP OLTP operation optimization pair of records perspective polygen polygen model polygen relation problem Proceedings QI-Compatible quality factors quality indicator quality parameters quality-merge statement query optimization R. Y. Wang Ramesh Patel record matching relational algebra relational model representation semantic Source Tagging specific Tayi techniques timeliness tion Total Data Quality tuples update views