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Books > Computing & IT > Applications of computing > Databases
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Handbook of Data Quality - Research and Practice (Hardcover, 2013 ed.)
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Handbook of Data Quality - Research and Practice (Hardcover, 2013 ed.)
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The issue of data quality is as old as data itself. Further, the
proliferation of quite diverse (e.g. in terms of structure or media
type) shared or public data on the Web has increased the risk of
poor data quality and false data aggregation. On the other hand,
data is now exposed at a much more strategic level e.g. through
business intelligence systems, increasing manifold the stakes
involved for corporations as well as government agencies. There,
the lack of knowledge about data accuracy, currency or completeness
can have erroneous and even catastrophic results. With these
changes, traditional approaches to data management in general, and
data quality control specifically, are challenged. There is an
evident need to incorporate data quality considerations into the
whole data cycle, encompassing managerial/governance as well as
technical aspects. Data quality experts from research and industry
agree that a unified framework for data quality management should
bring together organizational, architectural and computational
approaches. Accordingly, Sadiq structured this handbook in four
parts: Part I is on organizational solutions, i.e. the development
of data quality objectives for the organization, and the
development of strategies to establish roles, processes, policies,
and standards required to manage and ensure data quality. Part II,
on architectural solutions, covers the technology landscape
required to deploy developed data quality management processes,
standards and policies. Part III, on computational solutions,
presents effective and efficient IT tools and techniques related to
record linkage, lineage and provenance, data uncertainty, and
semantic integrity constraints. Finally, Part IV is devoted to case
studies of successful data quality initiatives that highlight the
various aspects of data quality in action. The individual chapters
present both an overview of the respective topic in terms of
historical research and/or practice and state of the art, as well
as specific techniques, methodologies and frameworks developed by
the individual contributors. Researchers and students of computer
science, information systems, or business management as well as
data professionals and practitioners will benefit most from this
handbook by not only focusing on the various sections relevant to
their research area or particular practical work, but by also
studying chapters that they may initially consider not to be
directly relevant to them, as there they will learn about new
perspectives and approaches.
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