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Competing with data quality : concepts, tools, and techniques for building a successful approach to data quality / Rajesh Jugulum.

By: Material type: TextTextPublisher: Hoboken, New Jersey : Wiley, 2014Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118420133
  • 1118420136
  • 9781118416495
  • 111841649X
Subject(s): Genre/Form: Additional physical formats: Print version:: Competing with data quality.DDC classification:
  • 004 23
LOC classification:
  • QA76.9.E95
Other classification:
  • BUS053000
Online resources: Summary: "Competing with Data Quality provides a road map for corporations to improve data quality and meet Dodd-Frank, BASEL III, Solvency II, and other pervasive regulatory oversight programs. This book outlines a holistic data quality (DQ) approach that businesses can adopt to energize their DQ innovation processes, perfect their data gathering and usage practices, and ensure robust and reliable data is available to make judicious decisions. It also addresses the end-to-end DQ deployment process: Define, Assess, Improve and Control. Numerous cases and "lessons learned" facilitate understanding"-- Provided by publisher.Summary: "This book aims at outlining a holistic data quality (DQ) approach that businesses can adopt to energize their DQ innovation processes, perfect their data gathering and usage practices and ensure robust and reliable data is available to make judicious decisions"-- Provided by publisher.
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Includes bibliographical references and index.

"Competing with Data Quality provides a road map for corporations to improve data quality and meet Dodd-Frank, BASEL III, Solvency II, and other pervasive regulatory oversight programs. This book outlines a holistic data quality (DQ) approach that businesses can adopt to energize their DQ innovation processes, perfect their data gathering and usage practices, and ensure robust and reliable data is available to make judicious decisions. It also addresses the end-to-end DQ deployment process: Define, Assess, Improve and Control. Numerous cases and "lessons learned" facilitate understanding"-- Provided by publisher.

"This book aims at outlining a holistic data quality (DQ) approach that businesses can adopt to energize their DQ innovation processes, perfect their data gathering and usage practices and ensure robust and reliable data is available to make judicious decisions"-- Provided by publisher.

Print version record and CIP data provided by publisher.

Economics