000			04011cam a2200349 a 4500
999			_c6889 _d6889
001			15236775
005			20210218135823.0
008			080328s2008 ne a b 001 0 eng d
010			_a 2008013824
020			_a9780123743695 (alk. paper)
020			_a0123743699 (alk. paper)
040			_aDLC _cDLC _dBTCTA _dBAKER _dYDXCP _dUKM _dC#P _dBWX _dDLC _erda
050	0	0	_aHD30.2 _b.M397 2008
082	0	0	_a658.404 _222 _bM.D.E
100	1		_aMcGilvray, Danette. _eauthor
245	1	0	_aExecuting data quality projects : _bten steps to quality data and trusted information / _cDanette McGilvray.
264		1	_aAmsterdam ; _aBoston : _bMorgan Kaufmann/Elsevier, _c[2008]
264		4	_a©2008.
300			_axviii, 325 pages : _billustrations ; _c28 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
504			_aIncludes bibliographical references (p. [303]-306) and index.
505	0		_aIntroduction -- The Reason for This Book -- Intended Audiences -- Structure of This Book -- How to Use This Book -- Acknowledgements -- Chapter 1 Overview -- Impact of Information and Data Quality -- About the Methodology -- Approaches to Data Quality in Projects -- Engaging Management -- Chapter 2 Key Concepts -- Introduction -- Framework for Information Quality (FIQ) -- Information Life Cycle -- Data Quality Dimensions -- Business Impact Techniques -- Data Categories -- Data Specifications -- Data Governance and Stewardship -- The Information and Data Quality Improvement Cycle -- The Ten StepsT Process -- Best Practices and Guidelines -- Chapter 3 The Ten Steps -- 1. Define Business Need and Approach -- 2. Analyze Information Environment -- 3. Assess Data Quality -- 4. Assess Business Impact -- 5. Identify Root Causes -- 6. Develop Improvement Plans -- 7. Prevent Future Data Errors -- 8. Correct Current Data Errors -- 9. Implement Controls -- 10. Communicate Actions and Results -- Chapter 4 Structuring Your Project -- Projects and The Ten Steps -- Data Quality Project Roles -- Project Timing -- Chapter 5 Other Techniques and Tools -- Introduction -- Information Life Cycle Approaches -- Capture Data -- Analyze and Document Results -- Metrics -- Data Quality Tools -- The Ten Steps and Six Sigma -- Chapter 6 A Few Final Words -- Appendix Quick References -- Framework for Information Quality -- POSMAD Interaction Matrix Detail -- POSMAD Phases and Activities -- Data Quality Dimensions -- Business Impact Techniques -- The Ten StepsT Overview -- Definitions of Data Categories.
520			_aData quality problems cost businesses billions of dollars each year in unnecessary printing, postage, and staffing costs, in the steady erosion of an organization's credibility among customers and suppliers, and the inability to make sound decisions. Danette McGilvray presents a systematic, proven approach to improving data quality by combining a conceptual framework for understanding information quality with techniques and instructions for improving it. The Ten Step approach applies to all types of data and to all types of organizations. * Includes numerous templates, detailed examples, and practical advice for executing every step of The Ten Steps approach. * Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices. * A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from The Ten Step methodology, and other tools and information that is available online.
650		0	_aInformation technology _xManagement.
650		0	_aElectronic data processing _xQuality control.
856	4	1	_3Table of contents only _uhttp://www.loc.gov/catdir/toc/ecip0814/2008013824.html
942			_cBK _2ddc