000			03150nam a2200493 i 4500
001			6267297
003			IEEE
005			20220712204623.0
006			m o d
007			cr |n|||||||||
008			151223s2009 maua ob 001 eng d
020			_z9780262513357 _qprint
020			_a9780262256544 _qebook
020			_z0262256541 _qelectronic
035			_a(CaBNVSL)mat06267297
035			_a(IDAMS)0b000064818b429f
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aHF5548.2 _b.J68 2006eb
082	0	4	_a658.4/038 _222
245	0	0	_aJourney to data quality / _cYang W. Lee ... [et al.].
264		1	_aCambridge, Massachusetts : _bMIT Press, _cc2006.
264		2	_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2009]
300			_a1 PDF (xii, 226 pages) : _billustrations.
336			_atext _2rdacontent
337			_aelectronic _2isbdmedia
338			_aonline resource _2rdacarrier
500			_a"Multi-User"
500			_aAcademic Complete Subscription 2011-2012
504			_aIncludes bibliographical references (p. [215]-221) and index.
506	1		_aRestricted to subscribers or individual electronic text purchasers.
520			_aAll organizations today confront data quality problems, both systemic and structural. Neither ad hoc approaches nor fixes at the systems level--installing the latest software or developing an expensive data warehouse--solve the basic problem of bad data quality practices. Journey to Data Quality offers a roadmap that can be used by practitioners, executives, and students for planning and implementing a viable data and information quality management program. This practical guide, based on rigorous research and informed by real-world examples, describes the challenges of data management and provides the principles, strategies, tools, and techniques necessary to meet them.The authors, all leaders in the data quality field for many years, discuss how to make the economic case for data quality and the importance of getting an organization's leaders on board. They outline different approaches for assessing data, both subjectively (by users) and objectively (using sampling and other techniques). They describe real problems and solutions, including efforts to find the root causes of data quality problems at a healthcare organization and data quality initiatives taken by a large teaching hospital. They address setting company policy on data quality and, finally, they consider future challenges on the journey to data quality.
530			_aAlso available in print.
538			_aMode of access: World Wide Web
588			_aDescription based on PDF viewed 12/23/2015.
650		0	_aBusiness _xData processing _xManagement. _922002
650		0	_aDatabase management _xQuality control. _922003
655		0	_aElectronic books. _93294
700	1		_aLee, Yang W. _922004
710	2		_aIEEE Xplore (Online Service), _edistributor. _922005
710	2		_aMIT Press, _epublisher. _922006
776	0	8	_iPrint version _z9780262513357
856	4	2	_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6267297
942			_cEBK
999			_c72954 _d72954