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Foundations of data quality management /

Bibliographic Details
Main Author: Fan, Wenfei
Other Authors: Geerts, Floris
Format: eBook
Language:English
Published: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, [2012]
Series:Synthesis lectures on data management ; #30.
Subjects:
Databases > Quality control.
Database management.
COMPUTERS / Programming Languages / SQL.
data quality
data consistency
data deduplication
data accuracy
information completeness
data currency
data dependencies
dependency discovery
rule validation
error detection
data repairing
master data
certain fixes
Electronic books.
Online Access:Connect to the full text of this electronic book
Connect to the full text of this electronic book
Description
Abstract:Data quality is one of the most important problems in data management. A database system typically aims to support the creation, maintenance, and use of large amount of data, focusing on the quantity of data. However, real-life data are often dirty: inconsistent, duplicated, inaccurate, incomplete, or stale. Dirty data in a database routinely generate misleading or biased analytical results and decisions, and lead to loss of revenues, credibility and customers. With this comes the need for data quality management. In contrast to traditional data management tasks, data quality management enables the detection and correction of errors in the data, syntactic or semantic, in order to improve the quality of the data and hence, add value to business processes.
Item Description:Electronic resource.
Physical Description:1 online resource (xv, 201 pages) : illustrations
Bibliography:Includes bibliographical references (pages 179-199).
ISBN:9781608457786 (electronic bk.)
1608457788 (electronic bk.)
ISSN:2153-5426 ;