Measuring Data Quality for Ongoing Improvement: A Data Quality Assessment Framework (Paperback)

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You'll 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. You'll 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 challenges






• Enables discussions between business and IT with a non-technical vocabulary for data quality measurement







• Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

《資料品質評估框架》向您展示如何測量和監控資料品質，確保長期的品質。您將從測量的一般概念開始，逐步深入了解與五個客觀品質維度相關的三十多種測量類型的詳細框架：完整性、及時性、一致性、有效性和完整性。持續的測量，而不僅僅是一次性活動，將幫助您的組織達到新的資料品質水平。這種以平易近人的方式來測量資料的方法可以被業務和IT理解，並提供實用指南，以在任何組織中應用DQAF，使您能夠優先考慮測量並有效地報告結果。書中還包括使用資料測量來管理和改善資料品質的策略，以及在資料資產中應用框架的指南。您將能夠優先考慮要實施的測量類型，知道在資料流中放置它們的位置以及測量的頻率。書中還包括用於定義和存儲資料品質結果以進行趨勢分析的常見概念模型，以及用於持續測量和監控的通用業務需求，包括使測量有意義並幫助理解趨勢和檢測異常的計算和比較方法。

該書還展示了如何利用與技術無關的資料品質測量框架來應對您特定的業務優先事項和資料品質挑戰。

該書使用非技術術語來進行資料品質測量，從而促進了業務和IT之間的討論。

該書描述了如何使用通用的測量類型來持續測量資料品質，這些測量類型可以應用於任何情況。