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Improving Data Warehouse and Business Information Quality

Improving Data Warehouse and Business Information Quality
Author: Larry P. English
Publisher: Wiley
Total Pages: 544
Release: 1999-03-25
Genre: Computers
ISBN: 9780471253839
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A comprehensive guide to quality improvement from the leading expert in information and data warehouse quality. Each year, companies lose millions as a result of inaccurate and missing data in their operational databases. This in turn corrupts data warehouses, causing them to fail. With information quality improvement and control systems, like the ones described in this book, your company can reduce costs and increase profits from quality information assets. Written by an internationally recognized expert in information quality improvement, Improving Data Warehouse and Business Information Quality arms you with a comprehensive set of tools and techniques for ensuring data quality both in source databases and the data warehouse. With the help of best-practices case studies, Larry English fills you in on: * How and when to measure information quality. * How to measure the business costs of poor quality information. * How to select the right information quality tools for your environment. * How to reengineer and cleanse data to improve the information product before it reaches your data warehouse. * How to improve the information creation processes at the source. * How to build quality controls into data warehouse processes. AUTHORBIO: Larry P. English is the leading international expert in the field of information and data warehouse quality. He is a columnist for Data Management Review and a featured speaker at numerous Data Warehousing Conferences. Larry chairs Information Quality Conferences held around the world.

Improving Data Warehouse and Business Information Quality

Improving Data Warehouse and Business Information Quality
Author: Larry P. English
Publisher: Wiley
Total Pages: 544
Release: 2011-02-11
Genre: Computers
ISBN: 9781118082072
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A comprehensive guide to quality improvement from the leading expert in information and data warehouse quality. Each year, companies lose millions as a result of inaccurate and missing data in their operational databases. This in turn corrupts data warehouses, causing them to fail. With information quality improvement and control systems, like the ones described in this book, your company can reduce costs and increase profits from quality information assets. Written by an internationally recognized expert in information quality improvement, Improving Data Warehouse and Business Information Quality arms you with a comprehensive set of tools and techniques for ensuring data quality both in source databases and the data warehouse. With the help of best-practices case studies, Larry English fills you in on: How and when to measure information quality. How to measure the business costs of poor quality information. How to select the right information quality tools for your environment. How to reengineer and cleanse data to improve the information product before it reaches your data warehouse. How to improve the information creation processes at the source. How to build quality controls into data warehouse processes. AUTHORBIO: Larry P. English is the leading international expert in the field of information and data warehouse quality. He is a columnist for Data Management Review and a featured speaker at numerous Data Warehousing Conferences. Larry chairs Information Quality Conferences held around the world.

Information Quality Applied

Information Quality Applied
Author: Larry P. English
Publisher: Wiley
Total Pages: 0
Release: 2009-10-12
Genre: Computers
ISBN: 9780470134474
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How to apply data quality management techniques to marketing, sales, and other specific business units Author and information quality management expert Larry English returns with a sequel to his much-acclaimed book, Improving Data Warehouse and Business Information Quality. In this new book he takes a hands-on approach, showing how to apply the concepts outlined in the first book to specific business areas like marketing, sales, finance, and human resources. The book presents real-world scenarios so you can see how to meld data quality concepts to specific business areas such as supply chain management, product and service development, customer care, and others. Step-by-step instruction, practical techniques, and helpful templates from the author help you immediately apply best practices and start modeling your own quality initiatives. Maintaining the quality and accuracy of business data is crucial; database managers are in need of specific guidance for data quality management in all key business areas Information Quality Applied offers IT, database, and business managers step-by-step instruction in setting up methodical and effective procedures The book provides specifics if you have to manage data quality in marketing, sales, customer care, supply chain management, product and service management, human resources, or finance The author includes templates that readers can put to immedate use for modeling their own quality initiatives A Companion Web site provides templates, updates to the book, and links to related sites

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
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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.

Executing Data Quality Projects

Executing Data Quality Projects
Author: Danette McGilvray
Publisher: Elsevier
Total Pages: 353
Release: 2008-09-01
Genre: Computers
ISBN: 0080558399
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Information is currency. Recent studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. In this important and timely new book, Danette McGilvray presents her “Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach—in which she has trained Fortune 500 clients and hundreds of workshop attendees—applies to all types of data and to all types of organizations. * Includes numerous templates, detailed examples, and practical advice for executing every step of the “Ten Steps approach.* Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices.* A companion Web site includes links to numerous data quality resources, including many of the planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.

Information Quality

Information Quality
Author: Richard Wang
Publisher: Routledge
Total Pages: 278
Release: 2014-12-18
Genre: Business & Economics
ISBN: 131746799X
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Organizations today have access to vast stores of data that come in a wide variety of forms and may be stored in places ranging from file cabinets to databases, and from library shelves to the Internet. The enormous growth in the quantity of data, however, has brought with it growing problems with the quality of information, further complicated by the struggles many organizations are experiencing as they try to improve their systems for knowledge management and organizational memory. Failure to manage information properly, or inaccurate data, costs businesses billions of dollars each year. This volume presents cutting-edge research on information quality. Part I seeks to understand how data can be measured and evaluated for quality. Part II deals with the problem of ensuring quality while processing data into information a company can use. Part III presents case studies, while Part IV explores organizational issues related to information quality. Part V addresses issues in information quality education.

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
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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

Enterprise Knowledge Management

Enterprise Knowledge Management
Author: David Loshin
Publisher: Morgan Kaufmann
Total Pages: 516
Release: 2001
Genre: Business & Economics
ISBN: 9780124558403
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This volume presents a methodology for defining, measuring and improving data quality. It lays out an economic framework for understanding the value of data quality, then outlines data quality rules and domain- and mapping-based approaches to consolidating enterprise knowledge.

Information and Database Quality

Information and Database Quality
Author: Mario G. Piattini
Publisher: Springer Science & Business Media
Total Pages: 240
Release: 2012-12-06
Genre: Computers
ISBN: 1461508312
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In a global and increasingly competitive market, where organizations are driven by information, the search for ways to transform data into true knowledge is critical to a business's success. Few companies, however, have effective methods of managing the quality of this information. Because quality is a multidimensional concept, its management must consider a wide variety of issues related to information and data quality. Information and Database Quality is a compilation of works from research and industry that examines these issues, covering both the organizational and technical aspects of information and data quality. Information and Database Quality is an excellent reference for both researchers and professionals involved in any aspect of information and database research.

Data and Information Quality

Data and Information Quality
Author: Carlo Batini
Publisher: Springer
Total Pages: 520
Release: 2016-03-23
Genre: Computers
ISBN: 3319241060
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This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.