Executing Data Quality Projects

Executing Data Quality Projects
Author: Danette McGilvray
Publsiher: Elsevier
Total Pages: 352
Release: 2008-09-01
ISBN: 0080558399
Category: Computers
Language: EN, FR, DE, ES & NL

Executing Data Quality Projects Book Excerpt:

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.

Executing Data Quality Projects

Executing Data Quality Projects
Author: Danette McGilvray
Publsiher: Academic Press
Total Pages: 376
Release: 2021-05-27
ISBN: 0128180161
Category: Computers
Language: EN, FR, DE, ES & NL

Executing Data Quality Projects Book Excerpt:

Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. 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. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today’s data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization’s standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach Contains real examples from around the world, gleaned from the author’s consulting practice and from those who implemented based on her training courses and the earlier edition of the book 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 templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online

Handbook of Data Quality

Handbook of Data Quality
Author: Shazia Sadiq
Publsiher: Springer Science & Business Media
Total Pages: 438
Release: 2013-08-13
ISBN: 3642362575
Category: Computers
Language: EN, FR, DE, ES & NL

Handbook of Data Quality Book Excerpt:

The issue of data quality is as old as data itself. However, the proliferation of diverse, large-scale and often publically available data on the Web has increased the risk of poor data quality and misleading data interpretations. On the other hand, data is now exposed at a much more strategic level e.g. through business intelligence systems, increasing manifold the stakes involved for individuals, corporations as well as government agencies. There, the lack of knowledge about data accuracy, currency or completeness can have erroneous and even catastrophic results. With these changes, traditional approaches to data management in general, and data quality control specifically, are challenged. There is an evident need to incorporate data quality considerations into the whole data cycle, encompassing managerial/governance as well as technical aspects. Data quality experts from research and industry agree that a unified framework for data quality management should bring together organizational, architectural and computational approaches. Accordingly, Sadiq structured this handbook in four parts: Part I is on organizational solutions, i.e. the development of data quality objectives for the organization, and the development of strategies to establish roles, processes, policies, and standards required to manage and ensure data quality. Part II, on architectural solutions, covers the technology landscape required to deploy developed data quality management processes, standards and policies. Part III, on computational solutions, presents effective and efficient tools and techniques related to record linkage, lineage and provenance, data uncertainty, and advanced integrity constraints. Finally, Part IV is devoted to case studies of successful data quality initiatives that highlight the various aspects of data quality in action. The individual chapters present both an overview of the respective topic in terms of historical research and/or practice and state of the art, as well as specific techniques, methodologies and frameworks developed by the individual contributors. Researchers and students of computer science, information systems, or business management as well as data professionals and practitioners will benefit most from this handbook by not only focusing on the various sections relevant to their research area or particular practical work, but by also studying chapters that they may initially consider not to be directly relevant to them, as there they will learn about new perspectives and approaches.

Measuring Data Quality for Ongoing Improvement

Measuring Data Quality for Ongoing Improvement
Author: Laura Sebastian-Coleman
Publsiher: Newnes
Total Pages: 376
Release: 2012-12-31
ISBN: 0123977541
Category: Computers
Language: EN, FR, DE, ES & NL

Measuring Data Quality for Ongoing Improvement Book Excerpt:

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

Executing Data Quality Projects

Executing Data Quality Projects
Author: Danette McGilvray
Publsiher: Unknown
Total Pages: 135
Release: 2008
ISBN: 9788131220412
Category: Electronic data processing
Language: EN, FR, DE, ES & NL

Executing Data Quality Projects Book Excerpt:

Making Enterprise Information Management EIM Work for Business

Making Enterprise Information Management  EIM  Work for Business
Author: John Ladley
Publsiher: Morgan Kaufmann
Total Pages: 552
Release: 2010-07-03
ISBN: 0123756960
Category: Computers
Language: EN, FR, DE, ES & NL

Making Enterprise Information Management EIM Work for Business Book Excerpt:

Making Enterprise Information Management (EIM) Work for Business: A Guide to Understanding Information as an Asset provides a comprehensive discussion of EIM. It endeavors to explain information asset management and place it into a pragmatic, focused, and relevant light. The book is organized into two parts. Part 1 provides the material required to sell, understand, and validate the EIM program. It explains concepts such as treating Information, Data, and Content as true assets; information management maturity; and how EIM affects organizations. It also reviews the basic process that builds and maintains an EIM program, including two case studies that provide a birds-eye view of the products of the EIM program. Part 2 deals with the methods and artifacts necessary to maintain EIM and have the business manage information. Along with overviews of Information Asset concepts and the EIM process, it discusses how to initiate an EIM program and the necessary building blocks to manage the changes to managed data and content. Organizes information modularly, so you can delve directly into the topics that you need to understand Based in reality with practical case studies and a focus on getting the job done, even when confronted with tight budgets, resistant stakeholders, and security and compliance issues Includes applicatory templates, examples, and advice for executing every step of an EIM program

MASTER DATA MANAGEMENT AND DATA GOVERNANCE 2 E

MASTER DATA MANAGEMENT AND DATA GOVERNANCE  2 E
Author: Alex Berson,Larry Dubov
Publsiher: McGraw Hill Professional
Total Pages: 512
Release: 2010-12-06
ISBN: 0071744592
Category: Computers
Language: EN, FR, DE, ES & NL

MASTER DATA MANAGEMENT AND DATA GOVERNANCE 2 E Book Excerpt:

The latest techniques for building a customer-focused enterprise environment "The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works." -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc. Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume. Plan and implement enterprise-scale MDM and Data Governance solutions Develop master data model Identify, match, and link master records for various domains through entity resolution Improve efficiency and maximize integration using SOA and Web services Ensure compliance with local, state, federal, and international regulations Handle security using authentication, authorization, roles, entitlements, and encryption Defend against identity theft, data compromise, spyware attack, and worm infection Synchronize components and test data quality and system performance

Data Quality

Data Quality
Author: Jack E. Olson
Publsiher: Morgan Kaufmann
Total Pages: 312
Release: 2003-01-09
ISBN: 9781558608917
Category: Computers
Language: EN, FR, DE, ES & NL

Data Quality Book Excerpt:

Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality. * Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes. * Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy. * Is written by one of the original developers of data profiling technology. * Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets.

Library Journal

Library Journal
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 2008
ISBN: 1928374650XXX
Category: Libraries
Language: EN, FR, DE, ES & NL

Library Journal Book Excerpt:

IDB Projects

IDB Projects
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 1997
ISBN: 1928374650XXX
Category: Economic development projects
Language: EN, FR, DE, ES & NL

IDB Projects Book Excerpt:

Pentaho Kettle Solutions

Pentaho Kettle Solutions
Author: Matt Casters,Roland Bouman,Jos van Dongen
Publsiher: John Wiley & Sons
Total Pages: 720
Release: 2010-09-28
ISBN: 0470635177
Category: Computers
Language: EN, FR, DE, ES & NL

Pentaho Kettle Solutions Book Excerpt:

A complete guide to Pentaho Kettle, the Pentaho Data lntegration toolset for ETL This practical book is a complete guide to installing, configuring, and managing Pentaho Kettle. If you’re a database administrator or developer, you’ll first get up to speed on Kettle basics and how to apply Kettle to create ETL solutions—before progressing to specialized concepts such as clustering, extensibility, and data vault models. Learn how to design and build every phase of an ETL solution. Shows developers and database administrators how to use the open-source Pentaho Kettle for enterprise-level ETL processes (Extracting, Transforming, and Loading data) Assumes no prior knowledge of Kettle or ETL, and brings beginners thoroughly up to speed at their own pace Explains how to get Kettle solutions up and running, then follows the 34 ETL subsystems model, as created by the Kimball Group, to explore the entire ETL lifecycle, including all aspects of data warehousing with Kettle Goes beyond routine tasks to explore how to extend Kettle and scale Kettle solutions using a distributed “cloud” Get the most out of Pentaho Kettle and your data warehousing with this detailed guide—from simple single table data migration to complex multisystem clustered data integration tasks.

Data Quality Assessment

Data Quality Assessment
Author: Arkady Maydanchik
Publsiher: Technics Publications
Total Pages: 336
Release: 2007-04-01
ISBN: 163462047X
Category: Computers
Language: EN, FR, DE, ES & NL

Data Quality Assessment Book Excerpt:

Imagine a group of prehistoric hunters armed with stone-tipped spears. Their primitive weapons made hunting large animals, such as mammoths, dangerous work. Over time, however, a new breed of hunters developed. They would stretch the skin of a previously killed mammoth on the wall and throw their spears, while observing which spear, thrown from which angle and distance, penetrated the skin the best. The data gathered helped them make better spears and develop better hunting strategies. Quality data is the key to any advancement, whether it’s from the Stone Age to the Bronze Age. Or from the Information Age to whatever Age comes next. The success of corporations and government institutions largely depends on the efficiency with which they can collect, organize, and utilize data about products, customers, competitors, and employees. Fortunately, improving your data quality doesn’t have to be such a mammoth task. DATA QUALITY ASSESSMENT is a must read for anyone who needs to understand, correct, or prevent data quality issues in their organization. Skipping theory and focusing purely on what is practical and what works, this text contains a proven approach to identifying, warehousing, and analyzing data errors – the first step in any data quality program. Master techniques in: • Data profiling and gathering metadata • Identifying, designing, and implementing data quality rules • Organizing rule and error catalogues • Ensuring accuracy and completeness of the data quality assessment • Constructing the dimensional data quality scorecard • Executing a recurrent data quality assessment This is one of those books that marks a milestone in the evolution of a discipline. Arkady's insights and techniques fuel the transition of data quality management from art to science -- from crafting to engineering. From deep experience, with thoughtful structure, and with engaging style Arkady brings the discipline of data quality to practitioners. David Wells, Director of Education, Data Warehousing Institute

Inter American Development Bank Monthly Operational Summary

Inter American Development Bank Monthly Operational Summary
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 2000
ISBN: 1928374650XXX
Category: Economic assistance
Language: EN, FR, DE, ES & NL

Inter American Development Bank Monthly Operational Summary Book Excerpt:

Meeting the Challenges of Data Quality Management

Meeting the Challenges of Data Quality Management
Author: Laura Sebastian-Coleman
Publsiher: Elsevier
Total Pages: 352
Release: 2022-02-15
ISBN: 0128217375
Category: Computers
Language: EN, FR, DE, ES & NL

Meeting the Challenges of Data Quality Management Book Excerpt:

Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its challenges. The book enables data management professionals to help their organizations get more value from data by addressing the five challenges of data quality management: the meaning challenge (recognizing how data represents reality), the process/quality challenge (creating high-quality data by design), the people challenge (building data literacy), the technical challenge (enabling organizational data to be accessed and used, as well as protected), and the accountability challenge (ensuring organizational leadership treats data as an asset). Organizations that fail to meet these challenges get less value from their data than organizations that address them directly. The book describes core data quality management capabilities and introduces new and experienced DQ practitioners to practical techniques for getting value from activities such as data profiling, DQ monitoring and DQ reporting. It extends these ideas to the management of data quality within big data environments. This book will appeal to data quality and data management professionals, especially those involved with data governance, across a wide range of industries, as well as academic and government organizations. Readership extends to people higher up the organizational ladder (chief data officers, data strategists, analytics leaders) and in different parts of the organization (finance professionals, operations managers, IT leaders) who want to leverage their data and their organizational capabilities (people, processes, technology) to drive value and gain competitive advantage. This will be a key reference for graduate students in computer science programs which normally have a limited focus on the data itself and where data quality management is an often-overlooked aspect of data management courses. Describes the importance of high-quality data to organizations wanting to leverage their data and, more generally, to people living in today's digitally interconnected world Explores the five challenges in relation to organizational data, including "Big Data," and proposes approaches to meeting them Clarifies how to apply the core capabilities required for an effective data quality management program (data standards definition, data quality assessment, monitoring and reporting, issue management, and improvement) as both stand-alone processes and as integral components of projects and operations Provides Data Quality practitioners with ways to communicate consistently with stakeholders

Astronomical Data Analysis Software and Systems XVII

Astronomical Data Analysis Software and Systems XVII
Author: Robert W. Argyle,Peter S. Bunclark,James R. Lewis
Publsiher: Astronomical Society of the pacific
Total Pages: 757
Release: 2008
ISBN: 9781583816585
Category: Computers
Language: EN, FR, DE, ES & NL

Astronomical Data Analysis Software and Systems XVII Book Excerpt:

Defense Modeling and Simulation Office Information Data Base Technology Working Group I DBTWG Meetings Held During the Week of July 11 15 1994

Defense Modeling and Simulation Office Information Data Base Technology Working Group  I DBTWG  Meetings Held During the Week of July 11 15  1994
Author: Defense Modeling and Simulation Office Information/Data Base (I/DB) Task Group,United States. Defense Modeling and Simulation Office. Information/Data Base Technology Working Group,Defense Modeling and Simulation Office Information/Data Base Technology Working Group
Publsiher: Unknown
Total Pages: 847
Release: 1994
ISBN: 1928374650XXX
Category: Computer simulation
Language: EN, FR, DE, ES & NL

Defense Modeling and Simulation Office Information Data Base Technology Working Group I DBTWG Meetings Held During the Week of July 11 15 1994 Book Excerpt:

This document contains the proceedings from the July 1994 Information/Data Base Technology Working Group meeting and related task force meetings. RAND participated in this effort at the request of the Director, Defense Modeling and Simulation Office.

Marketing Research

Marketing Research
Author: Melvin Crask,Richard J. Fox
Publsiher: Allyn & Bacon
Total Pages: 642
Release: 1995
ISBN: 1928374650XXX
Category: Marketing Research
Language: EN, FR, DE, ES & NL

Marketing Research Book Excerpt:

Manual para la investigación del marketing destinado a estudiantes de iniciación con la finalidad de insertarlos en la asignatura y en la comprensión de los principales conceptos. Se incluyen dos caso prácticos por cada capítulo.

Development Business

Development Business
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 2004-07
ISBN: 1928374650XXX
Category: Economic assistance
Language: EN, FR, DE, ES & NL

Development Business Book Excerpt:

Guide for Conducting Treatability Studies Under CERCLA

Guide for Conducting Treatability Studies Under CERCLA
Author: Anonim
Publsiher: Unknown
Total Pages: 118
Release: 1990
ISBN: 1928374650XXX
Category: Environmental impact analysis
Language: EN, FR, DE, ES & NL

Guide for Conducting Treatability Studies Under CERCLA Book Excerpt:

Target setting Methods and Data Management to Support Performance based Resource Allocation by Transportation Agencies

Target setting Methods and Data Management to Support Performance based Resource Allocation by Transportation Agencies
Author: National Cooperative Highway Research Program
Publsiher: Transportation Research Board National Research
Total Pages: 128
Release: 2010
ISBN: 9780309155007
Category: Resource allocation
Language: EN, FR, DE, ES & NL

Target setting Methods and Data Management to Support Performance based Resource Allocation by Transportation Agencies Book Excerpt:

TRB's National Cooperative Highway Research Program (NCHRP) Report 666: Target Setting Methods and Data Management to Support Performance-Based Resource Allocation by Transportation Agencies - Volume I: Research Report, and Volume II: Guide for Target-Setting and Data Management provides a framework and specific guidance for setting performance targets and for ensuring that appropriate data are available to support performance-based decision-making. Volume III to this report was published separately in an electronic-only format as NCHRP Web-Only Document 154. Volume III includes case studies of organizations investigated in the research used to develop NCHRP Report 666.