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Enterprise knowledge management : the data quality approach /
Today, 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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
San Diego :
Morgan Kaufmann,
©2001.
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| Colección: | Morgan Kaufmann Series in Data Management Systems Ser.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- Preface
- 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.