000			03714cam a22003614a 4500
003			OSt
005			20220707134206.0
020			_a9780124558403
040			_aDLC _cDLC _dDLC _bEng _erda
041			_aEng
042			_apcc
050	0	0	_aHD30.2 _bLOS
100	1		_aLoshin, David, _eAuthor
245	1	0	_aEnterprise knowledge management : _bthe data quality approach / _cDavid Loshin.
260			_aSan Diego : _bMorgan Kaufmann, _c2001.
300			_axviii, 493 pages : _billustrations;
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
490			_aMorgan Kaufmann Series in Data Management Systems Ser.
500			_aIncludes index.
505			_aPreface -- Chapter 1 -- Introduction -- Chapter 2 -- Who Owns Information? -- Chapter 3 -- Data Quality in Practice -- Chapter 4 -- Economic Framework of Data Quality and the Value Proposition -- Chapter 5 -- Dimensions of Data Quality -- Chapter 6 -- Statistical Process Control and the Improvement Cycle -- Chapter 7 -- Domains, Mappings, and Enterprise Reference Data -- Chapter 8 -- Data Quality Assertions and Business Rules -- Chapter 9 -- Measurement and Current State Assessment -- Chapter 10 -- Data Quality Requirements -- Chapter 11 -- Metadata, Guidelines, and Policy -- Chapter 12 -- Rule-Based Data Quality -- Chapter 13 -- Metadata and Rule Discovery -- Chapter 14 -- Data Cleansing -- Chapter 15 -- Root Cause Analysis and Supplier Management -- Chapter 16 -- Data Enrichment/Enhancement -- Chapter 17 -- Data Quality and Business Rules in Practice -- Chapter 18 -- Building the Data Quality Practice.
520			_aToday, companies capture and store tremendous amounts of information about every aspect of their business: their customers, partners, vendors, markets, and more. But with the rise in the quantity of information has come a corresponding decrease in its quality--a problem businesses recognize and are working feverishly to solve. Enterprise Knowledge Management: The Data Quality Approach presents an easily adaptable methodology for defining, measuring, and improving data quality. Author David Loshin begins by presenting an economic framework for understanding the value of data quality, then proceeds to outline data quality rules and domain-and mapping-based approaches to consolidating enterprise knowledge. Written for both a managerial and a technical audience, this book will be indispensable to the growing number of companies committed to wresting every possible advantage from their vast stores of business information. Key Features * Expert advice from a highly successful data quality consultant * The only book on data quality offering the business acumen to appeal to managers and the technical expertise to appeal to IT professionals * Details the high costs of bad data and the options available to companies that want to transform mere data into true enterprise knowledge * Presents conceptual and practical information complementing companies' interest in data warehousing, data mining, and knowledge discovery.
650		0	_aKnowledge management.
650		0	_aIndustrial management _xData processing.
650		0	_aInformation technology _xManagement.
650		0	_aBusiness enterprises _xData processing _xManagement.
856	4	2	_uhttp://www.loc.gov/catdir/description/els031/00112074.html
856	4	1	_uhttp://www.loc.gov/catdir/toc/els031/00112074.html
906			_a7 _bcbc _corignew _d2 _eepcn _f20 _gy-gencatlg
942			_2lcc _cBK
999			_c3092 _d3092