000			05224nam a22005175i 4500
001			978-3-642-36257-6
003			DE-He213
005			20200421111704.0
007			cr nn 008mamaa
008			130508s2013 gw | s |||| 0|eng d
020			_a9783642362576 _9978-3-642-36257-6
024	7		_a10.1007/978-3-642-36257-6 _2doi
050		4	_aQA76.9.D3
072		7	_aUN _2bicssc
072		7	_aUMT _2bicssc
072		7	_aCOM021000 _2bisacsh
082	0	4	_a005.74 _223
245	1	0	_aHandbook of Data Quality _h[electronic resource] : _bResearch and Practice / _cedited by Shazia Sadiq.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013.
300			_aXII, 438 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aResearch and Practice in Data Quality Management -- Data Quality Management Past, Present, and Future: Towards a Management System for Data -- Data Quality Projects and Programs -- On the Evolution of Data Governance in Firms: The Case of Johnson & Johnson Consumer Products North America -- Cost and Value Management for Data Quality -- Data Warehouse Quality: Summary and Outlook -- Using Semantic Web Technologies for Data Quality Management -- Data Glitches: Monsters in your Data -- Generic and Declarative Approaches to Data Quality Management -- Linking Records in Complex Context -- A Practical Guide to Entity Resolution with OYSTER -- Managing Quality of Probabilistic Databases -- Data Fusion: Resolving Conflicts from Multiple Sources -- Ensuring the Quality of Health Information: The Canadian Experience -- Shell's Global Data Quality Journey -- Creating an Information Centric Organisation Culture at SBI General Insurance -- Epilogue: The Data Quality Profession.
520			_aThe issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. 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 individuals, 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 tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced 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.
650		0	_aComputer science.
650		0	_aManagement information systems.
650		0	_aFile organization (Computer science).
650		0	_aDatabase management.
650		0	_aInformation storage and retrieval.
650	1	4	_aComputer Science.
650	2	4	_aDatabase Management.
650	2	4	_aInformation Storage and Retrieval.
650	2	4	_aManagement of Computing and Information Systems.
650	2	4	_aFiles.
650	2	4	_aBusiness IT Infrastructure.
700	1		_aSadiq, Shazia. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642362569
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-36257-6
912			_aZDB-2-SCS
942			_cEBK
999			_c55128 _d55128