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Information Quality Applied: Best Practices for Improving Business Information, Processes and Systems
book

Information Quality Applied: Best Practices for Improving Business Information, Processes and Systems

by Larry P. English
October 2009
Beginner to intermediate content levelBeginner to intermediate
839 pages
29h 16m
English
Wiley
Content preview from Information Quality Applied: Best Practices for Improving Business Information, Processes and Systems
Chapter 8 n Data Correction and Controlling Data Redundancy 337
Objectives
There are six major objectives for data correction:
Correct Errors and Information Defects in operational source Databases
■n
that cause processes to fail.
Correct Errors in Data provided by Third-Party Brokers or Business
■n
Partners to prevent retrieval and application processes from failing.
Prepare and transform data required for conversion to new Information
■n
Systems or purchased Software Package Databases.
Consolidate and transform data required by
■n
mergers and acquisitions, where
data must be “integrated” (transformed or consolidated) into an Enterprise
Database.
Prepare and correct data
■n
required for data mining for decision analysis,
where errors and omissions will cause the analysis to fail.
Correct and transform data in the Source Database(s) prior to propagating
■n
them to a Strategic Database (data warehouse).
Avoiding Pitfalls
Do not rely on data correction for solving the Information Quality problems in
your organization. Your core competency must be TIQM Process P4 Improve
Information Process Quality.
Conduct a Data Correction Activity
■n
as a one-time event for any given data
store, after you have identified Root Causes and Improved and Error-
Proofed the Defective Process.
Always correct data in its Source Data Store and
■n
propagate the corrections
to any required, redundant Data Stores. The reasons ...
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Publisher Resources

ISBN: 9780470134474Purchase book