The practitioner's guide to data quality improvement /

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Business problems are directly related to missed data quality expectations. Flawed information production processes introduce risks preventing the successful achievement of critical business objectives. However, these flaws are mitigated through data quality management and control: controlling the q...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Loshin, David, 1963-
Format: Electronic eBook
Language:Inglés
Published: Burlington, MA : Morgan Kaufmann, ©2011.
Subjects:
Database management > Quality control.
Databases > Quality control.
Bases de données > Gestion > Qualité > Contrôle.
COMPUTERS > Desktop Applications > Databases.
COMPUTERS > Database Management > General.
COMPUTERS > System Administration > Storage & Retrieval.
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • Business impacts of poor data quality
  • The organizational data quality program
  • Data quality maturity
  • Enterprise initiative integration
  • Developing a business case and a data quality road map
  • Metrics and performance improvement
  • Data governance
  • Dimensions of data quality
  • Data requirement analysis
  • Metadata and data standards
  • Data quality assessment
  • Remediation and improvement planning
  • Data quality service level agreements
  • Data profiling
  • Parsing and standardization
  • Entity identity resolution
  • Inspection, monitoring, auditing, and tracking
  • Data enhancement
  • Master data management and data quality
  • Bringing it all together.

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