Enterprise knowledge management : the data quality approach /

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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...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Loshin, David, 1963-
Format: Electronic eBook
Language:Inglés
Published: San Diego : Morgan Kaufmann, ©2001.
Series:Morgan Kaufmann Series in Data Management Systems Ser.
Subjects:
Knowledge management.
Industrial management > Data processing.
Information technology > Management.
Business enterprises > Data processing > Management.
Knowledge Management
Gestion des connaissances.
Gestion > Informatique.
Technologie de l'information > Gestion.
Entreprises > Informatique > Gestion.
Data-Warehouse-Konzept
Informationsmanagement
Wissensmanagement
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • 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.

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