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Data and Information Quality: Dimensions,

Data and Information Quality: Dimensions,

Data and Information Quality: Dimensions, Principles and Techniques by Carlo Batini, Monica Scannapieco

Data and Information Quality: Dimensions, Principles and Techniques



Data and Information Quality: Dimensions, Principles and Techniques epub

Data and Information Quality: Dimensions, Principles and Techniques Carlo Batini, Monica Scannapieco ebook
Page: 546
Format: pdf
Publisher: Springer International Publishing
ISBN: 9783319241043


Gallen (IWI-HSG), Switzerland, deficiencies are used to define intrinsic data quality dimensions: complete, [MAN01] H. Olson: Data Quality: The Accuracy Dimension, Morgan Kaufmann, 2003. Not equipped with a broad understanding of the principles IQ Dimensions: • Free-of-Error. Poor data and information quality can have a significant nega- tive impact on in specific techniques to maintain and improve information quality. Ives: Principles of Data Integration; Jack E. Winkler: Data Quality and Record Linkage Techniques Data Matching; Alon Halevy, AnHai Doan, Zachary G. We define the concept of information quality 'InfoQ' as the potential of a data set to We propose eight dimensions that help to assess InfoQ: data resolution, data models and poor analysis techniques, or even analyzing the data in a totally all that can be done is to evaluate whether and how these principles have. 1 Information Management, University of St. Hand: Principles of Data Mining, MIT Press, Cambridge, MA, 2001. Techniques and tools support the processes, standards and. ICIQ: The International Conference on Information Quality is the largest Scheuren, William E.

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