Measuring Data Quality for Ongoing Improvement: A Data Quality Assessment Framework

丛 书 名：The Morgan Kaufmann Series on Business Intelligence

作     者：Sebastian-Coleman, Laura 

I S B N：(纸本) 9780123970336 

出 版 社：Morgan Kaufmann_RM 

出 版 年：2012年

主 题 词：Computer Science and Technology 

学科分类：0810[工学-信息与通信工程] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0835[工学-软件工程] 081002[工学-信号与信息处理] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

摘      要：The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. Youl start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. Youl come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challengesEnables discussions between business and IT with a non-technical vocabulary for data quality measurementDescribes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation