Data Quality: Concepts, Methodologies and Techniques by Carlo Batini

By Carlo Batini

Poor facts caliber can heavily prevent or harm the potency and effectiveness of businesses and companies. The starting to be expertise of such repercussions has resulted in significant public projects just like the "Data caliber Act" within the united states and the "European 2003/98" directive of the eu Parliament.

Batini and Scannapieco current a finished and systematic advent to the extensive set of concerns regarding info caliber. they begin with a close description of other information caliber dimensions, like accuracy, completeness, and consistency, and their value in numerous different types of info, like federated info, net information, or time-dependent info, and in numerous information different types labeled in accordance with frequency of switch, like good, long term, and often altering information. The book's wide description of strategies and methodologies from middle info caliber study in addition to from comparable fields like info mining, likelihood conception, statistical information research, and computing device studying provides a great assessment of the present state-of-the-art. The presentation is done via a brief description and significant comparability of instruments and functional methodologies, so that it will aid readers to solve their very own caliber problems.

This ebook is a perfect mixture of the steadiness of theoretical foundations and the applicability of sensible ways. it truly is preferrred for everybody – researchers, scholars, or pros – drawn to a entire evaluate of information caliber matters. furthermore, it's going to function the root for an introductory direction or for self-study in this topic.

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Some other proposals are related to specific domains that need ad hoc dimensions in order to capture the peculiarities of the domain. 5 Other Data Quality Dimensions 33 1. The archival domain (see [217] and [111]) and the Interpares project [101], which makes use of dimensions such as condition (of a document) that refers to the physical suitability of the document for scanning. 2. The statistical domain; every National bureau of census and international organizations such as the European Union or the International Monetary Fund define several dimensions for statistical and scientific data (see [96]), such as integrity, on the notion that statistical systems should be based on adherence to the principle of objectivity in the collection, compilation, and dissemination of statistics.

The traditional completeness dimension provides only a static characterization of completeness. In order to consider the temporal dynamics of completeness, as needed in Web information systems, we introduce the notion of completability. We consider a function C(t), defined as the value of completeness at the instant t, with t ∈ [t pub, t max], where t pub is the initial instant of publication of data and t max corresponds to the maximum time within which the series of the different scheduled updates will be completed.

StudentID Name Surname Vote ExaminationDate 6754 Mike Collins 29 07/17/2004 8907 Anne Herbert 18 07/17/2004 6578 Julianne Merrals NULL 07/17/2004 0987 Robert Archer NULL NULL 1243 Mark Taylor 26 09/30/2004 2134 Bridget Abbott 30 09/30/2004 6784 John Miller 30 NULL 0098 Carl Adams 25 09/30/2004 1111 John Smith 28 09/30/2004 2564 Edward Monroe NULL NULL 8976 Anthony White 21 NULL 8973 Marianne Collins 30 10/15/2004 Fig. 4. Student relation exemplifying the completeness of tuples, attributes and relations.

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