Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement
Author: Laura Sebastian-Coleman
Publisher: Newnes
Total Pages: 404
Release: 2012-12-31
Genre: Computers
ISBN: 0123977541

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

Data Quality

Data Quality
Author: Rupa Mahanti
Publisher: Quality Press
Total Pages: 526
Release: 2019-03-18
Genre: Business & Economics
ISBN: 0873899776

“This is not the kind of book that you’ll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective.” from the foreword by Thomas C. Redman, Ph.D., “the Data Doc” Good data is a source of myriad opportunities, while bad data is a tremendous burden. Companies that manage their data effectively are able to achieve a competitive advantage in the marketplace, while bad data, like cancer, can weaken and kill an organization. In this comprehensive book, Rupa Mahanti provides guidance on the different aspects of data quality with the aim to be able to improve data quality. Specifically, the book addresses: -Causes of bad data quality, bad data quality impacts, and importance of data quality to justify the case for data quality-Butterfly effect of data quality-A detailed description of data quality dimensions and their measurement-Data quality strategy approach-Six Sigma - DMAIC approach to data quality-Data quality management techniques-Data quality in relation to data initiatives like data migration, MDM, data governance, etc.-Data quality myths, challenges, and critical success factorsStudents, academicians, professionals, and researchers can all use the content in this book to further their knowledge and get guidance on their own specific projects. It balances technical details (for example, SQL statements, relational database components, data quality dimensions measurements) and higher-level qualitative discussions (cost of data quality, data quality strategy, data quality maturity, the case made for data quality, and so on) with case studies, illustrations, and real-world examples throughout.

The Practitioner's Guide to Data Quality Improvement

The Practitioner's Guide to Data Quality Improvement
Author: David Loshin
Publisher: Elsevier
Total Pages: 423
Release: 2010-11-22
Genre: Computers
ISBN: 0080920349

The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning.

Multi-Domain Master Data Management

Multi-Domain Master Data Management
Author: Mark Allen
Publisher: Morgan Kaufmann
Total Pages: 244
Release: 2015-03-21
Genre: Computers
ISBN: 0128011475

Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration. Provides a logical order toward planning, implementation, and ongoing management of multi-domain MDM from a program manager and data steward perspective. Provides detailed guidance, examples and illustrations for MDM practitioners to apply these insights to their strategies, plans, and processes. Covers advanced MDM strategy and instruction aimed at improving data quality management, lowering data maintenance costs, and reducing corporate risks by applying consistent enterprise-wide practices for the management and control of master data.

Statistical Methods for Quality Assurance

Statistical Methods for Quality Assurance
Author: Stephen B. Vardeman
Publisher: Springer
Total Pages: 447
Release: 2016-08-26
Genre: Mathematics
ISBN: 038779106X

This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings

Data Quality

Data Quality
Author: Richard Y. Wang
Publisher: Springer Science & Business Media
Total Pages: 175
Release: 2006-04-11
Genre: Computers
ISBN: 0306469871

Data Quality provides an exposé of research and practice in the data quality field for technically oriented readers. It is based on the research conducted at the MIT Total Data Quality Management (TDQM) program and work from other leading research institutions. This book is intended primarily for researchers, practitioners, educators and graduate students in the fields of Computer Science, Information Technology, and other interdisciplinary areas. It forms a theoretical foundation that is both rigorous and relevant for dealing with advanced issues related to data quality. Written with the goal to provide an overview of the cumulated research results from the MIT TDQM research perspective as it relates to database research, this book is an excellent introduction to Ph.D. who wish to further pursue their research in the data quality area. It is also an excellent theoretical introduction to IT professionals who wish to gain insight into theoretical results in the technically-oriented data quality area, and apply some of the key concepts to their practice.

Handbook of Micrometeorology

Handbook of Micrometeorology
Author: Xuhui Lee
Publisher: Springer Science & Business Media
Total Pages: 261
Release: 2006-01-20
Genre: Science
ISBN: 1402022654

The Handbook of Micrometeorology is the most up-to-date reference for micrometeorological issues and methods related to the eddy covariance technique for estimating mass and energy exchange between the terrestrial biosphere and the atmosphere. It provides useful insight for interpreting estimates of mass and energy exchange and understanding the role of the terrestrial biosphere in global environmental change.

Quality Assurance of Chemical Measurements

Quality Assurance of Chemical Measurements
Author: John K. Taylor
Publisher: CRC Press
Total Pages: 354
Release: 1987-08-02
Genre: Science
ISBN: 9780873710978

This definitive new book should appeal to everyone who produces, uses, or evaluates scientific data. Ensures accuracy and reliability. Dr. Taylor's book provides guidance for the development and implementation of a credible quality assurance program, plus it also provides chemists and clinical chemists, medical and chemical researchers, and all scientists and managers the ideal means to ensure accurate and reliable work. Chapters are presented in a logical progression, starting with the concept of quality assurance, principles of good measurement, principles of quality assurance, and evaluation of measurement quality. Each chapter has a degree of independence so that it may be consulted separately from the others.