The Practitioners Guide To Data Quality Improvement

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.

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

Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780123737175 .

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.

Never HIGHLIGHT a Book Again Virtually all testable terms, concepts, persons, places, and events are included. Cram101 Textbook Outlines gives all of the outlines, highlights, notes for your textbook with optional online practice tests. Only Cram101 Outlines are Textbook Specific. Cram101 is NOT the Textbook. Accompanys: 9780521673761

Data governance looks simple on paper, but in reality it is a complex issue facing organizations. In this practical guide, data experts Uma Gupta and San Cannon look to demystify data governance through pragmatic advice based on real-world experience and cutting-edge academic research.

This hands-on book presents a complete understanding of SixSigma and Lean Six Sigma through data analysis and statisticalconcepts In today's business world, Six Sigma, or Lean Six Sigma, is acrucial tool utilized by companies to improve customersatisfaction, increase profitability, and enhance productivity.Practitioner's Guide to Statistics and Lean Six Sigma forProcess Improvements provides a balanced approach toquantitative and qualitative statistics using Six Sigma and LeanSix Sigma methodologies. Emphasizing applications and the implementation of data analysesas they relate to this strategy for business management, this bookintroduces readers to the concepts and techniques for solvingproblems and improving managerial processes using Six Sigma andLean Six Sigma. Written by knowledgeable professionals working inthe field today, the book offers thorough coverage of thestatistical topics related to effective Six Sigma and Lean SixSigma practices, including: Discrete random variables and continuous random variables Sampling distributions Estimation and hypothesis tests Chi-square tests Analysis of variance Linear and multiple regression Measurement analysis Survey methods and sampling techniques The authors provide numerous opportunities for readers to testtheir understanding of the presented material, as the real datasets, which are incorporated into the treatment of each topic, canbe easily worked with using Microsoft Office Excel, Minitab,MindPro, or Oracle's Crystal Ball software packages. Examples ofsuccessful, complete Six Sigma and Lean Six Sigma projects aresupplied in many chapters along with extensive exercises that rangein level of complexity. The book is accompanied by an extensive FTPsite that features manuals for working with the discussed softwarepackages along with additional exercises and data sets. Inaddition, numerous screenshots and figures guide readers throughthe functional and visual methods of learning Six Sigma and LeanSix Sigma. Practitioner's Guide to Statistics and Lean Six Sigma forProcess Improvements is an excellent book for courses on SixSigma and statistical quality control at the upper-undergraduateand graduate levels. It is also a valuable reference forprofessionals in the fields of engineering, business, physics,management, and finance.

Through a unique interdisciplinary perspective on quality management in health care, this text covers the subjects of operations management, organizational behavior, and health services research. With a particular focus on Total Quality Management (TQM) and Continuous Quality Improvement (CQI), the challenges of implementation and institutionalization are addressed using examples from a variety of health care organizations, including primary care clinics, hospital laboratories, public health departments, and academic health centers. Significantly revised throughout, the Fifth Edition offers a greater focus on application techniques, and features 14 chapters in lieu of the prior edition's 20 chapters, making it an even more effective teaching tool. New chapters have been incorporated on Implementation Science (3), Lean Six Sigma (6), and Classification and the Reduction of Medical Errors (10).