Enterprise Knowledge Management. The Data Quality Approach

✍ Scribed by David Loshin (Auth.)

Publisher: Morgan Kaufmann
Year: 2001
Tongue: English
Leaves: 491
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Content:
Preface, Pages xiii-xviii
1 - Introduction, Pages 1-24
2 - Who owns information?, Pages 25-46
3 - Data quality in practice, Pages 47-72
4 - Economic framework of data quality and the value proposition, Pages 73-99
5 - Dimensions of data quality, Pages 101-124
6 - Statistical process control and the improvement cycle, Pages 125-141
7 - Domains, mappings, and enterprise reference data, Pages 143-168
8 - Data quality assertions and business rules, Pages 169-201
9 - Measurement and current state assessment, Pages 203-231
10 - Data quality requirements, Pages 233-251
11 - Metadata, guidelines, and policy, Pages 253-277
12 - Rule-based data quality, Pages 279-300
13 - Metadata and rule discovery, Pages 301-331
14 - Data cleansing, Pages 333-380
15 - Root cause analysis and supplier management, Pages 381-397
16 - Data enrichment/enhancement, Pages 399-424
17 - Data quality and business rules in practice, Pages 425-461
18 - Building the data quality practice, Pages 463-484
Index, Pages 485-493
Bibliography, Page 494

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