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Executing Data Quality Projects

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Executing Data Quality Projects

Executing Data Quality Projects Book
Author : Danette McGilvray
Publisher : Elsevier
Release : 2008-09-01
ISBN : 0080558399
Language : En, Es, Fr & De

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Book Description :

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 Book
Author : Danette McGilvray
Publisher : Academic Press
Release : 2021-05-27
ISBN : 0128180161
Language : En, Es, Fr & De

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Book Description :

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

Executing Data Quality Projects

Executing Data Quality Projects Book
Author : Danette McGilvray
Publisher : Unknown
Release : 2008
ISBN : 9788131220412
Language : En, Es, Fr & De

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Book Description :

Download Executing Data Quality Projects book written by Danette McGilvray, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Handbook of Data Quality

Handbook of Data Quality Book
Author : Shazia Sadiq
Publisher : Springer Science & Business Media
Release : 2013-08-13
ISBN : 3642362575
Language : En, Es, Fr & De

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Book Description :

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 Book
Author : Laura Sebastian-Coleman
Publisher : Newnes
Release : 2012-12-31
ISBN : 0123977541
Language : En, Es, Fr & De

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Book Description :

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

Competing with High Quality Data

Competing with High Quality Data Book
Author : Rajesh Jugulum
Publisher : John Wiley & Sons
Release : 2014-03-10
ISBN : 111841649X
Language : En, Es, Fr & De

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Book Description :

Create a competitive advantage with data quality Data is rapidly becoming the powerhouse of industry, butlow-quality data can actually put a company at a disadvantage. Tobe used effectively, data must accurately reflect the real-worldscenario it represents, and it must be in a form that is usable andaccessible. Quality data involves asking the right questions,targeting the correct parameters, and having an effective internalmanagement, organization, and access system. It must be relevant,complete, and correct, while falling in line with pervasiveregulatory oversight programs. Competing with High Quality Data: Concepts, Tools andTechniques for Building a Successful Approach to Data Qualitytakes a holistic approach to improving data quality, fromcollection to usage. Author Rajesh Jugulum is globally-recognizedas a major voice in the data quality arena, with high-levelbackgrounds in international corporate finance. In the book,Jugulum provides a roadmap to data quality innovation,covering topics such as: The four-phase approach to data quality control Methodology that produces data sets for different aspects of abusiness Streamlined data quality assessment and issue resolution A structured, systematic, disciplined approach to effectivedata gathering The book also contains real-world case studies to illustrate howcompanies across a broad range of sectors have employed dataquality systems, whether or not they succeeded, and what lessonswere learned. High-quality data increases value throughout theinformation supply chain, and the benefits extend to the client,employee, and shareholder. Competing with High Quality Data:Concepts, Tools and Techniques for Building a Successful Approachto Data Quality provides the information and guidance necessaryto formulate and activate an effective data quality plan today.

Making Enterprise Information Management EIM Work for Business

Making Enterprise Information Management  EIM  Work for Business Book
Author : John Ladley
Publisher : Morgan Kaufmann
Release : 2010-07-03
ISBN : 0123756960
Language : En, Es, Fr & De

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Book Description :

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

Integration of Data Mining in Business Intelligence Systems

Integration of Data Mining in Business Intelligence Systems Book
Author : Azevedo, Ana
Publisher : IGI Global
Release : 2014-09-30
ISBN : 1466664789
Language : En, Es, Fr & De

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Book Description :

Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

Recent Trends in Data Science and Soft Computing

Recent Trends in Data Science and Soft Computing Book
Author : Faisal Saeed,Nadhmi Gazem,Fathey Mohammed,Abdelsalam Busalim
Publisher : Springer
Release : 2018-09-08
ISBN : 3319990071
Language : En, Es, Fr & De

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Book Description :

This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial Intelligence and Soft Computing, Business Intelligence, Internet of Things (IoT) Technologies and Applications, Intelligent Communication Systems, Advances in Computer Vision, Health Informatics, Reliable Cloud Computing Environments, Recent Trends in Knowledge Management, Security Issues in the Cyber World, and Advances in Information Systems Research, Theories and Methods.

Information Quality and Governance for Business Intelligence

Information Quality and Governance for Business Intelligence Book
Author : Yeoh, William
Publisher : IGI Global
Release : 2013-12-31
ISBN : 1466648937
Language : En, Es, Fr & De

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Book Description :

Business intelligence initiatives have been dominating the technology priority list of many organizations. However, the lack of effective information quality and governance strategies and policies has been meeting these initiatives with some challenges. Information Quality and Governance for Business Intelligence presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth. This book is an essential reference tool for researchers, practitioners, and university students specializing in business intelligence, information quality, and information systems.

Data Quality

Data Quality Book
Author : Rupa Mahanti
Publisher : Quality Press
Release : 2019-03-18
ISBN : 0873899776
Language : En, Es, Fr & De

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Book Description :

“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.

Entity Resolution and Information Quality

Entity Resolution and Information Quality Book
Author : John R. Talburt
Publisher : Elsevier
Release : 2011-01-14
ISBN : 9780123819734
Language : En, Es, Fr & De

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Book Description :

Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a very wide view of IQ, including its six-domain framework and the skills formed by the International Association for Information and Data Quality {IAIDQ). The book includes chapters that cover the principles of entity resolution and the principles of Information Quality, in addition to their concepts and terminology. It also discusses the Fellegi-Sunter theory of record linkage, the Stanford Entity Resolution Framework, and the Algebraic Model for Entity Resolution, which are the major theoretical models that support Entity Resolution. In relation to this, the book briefly discusses entity-based data integration (EBDI) and its model, which serve as an extension of the Algebraic Model for Entity Resolution. There is also an explanation of how the three commercial ER systems operate and a description of the non-commercial open-source system known as OYSTER. The book concludes by discussing trends in entity resolution research and practice. Students taking IT courses and IT professionals will find this book invaluable. First authoritative reference explaining entity resolution and how to use it effectively Provides practical system design advice to help you get a competitive advantage Includes a companion site with synthetic customer data for applicatory exercises, and access to a Java-based Entity Resolution program.

Integration Challenges for Analytics Business Intelligence and Data Mining

Integration Challenges for Analytics  Business Intelligence  and Data Mining Book
Author : Azevedo, Ana,Santos, Manuel Filipe
Publisher : IGI Global
Release : 2020-12-11
ISBN : 1799857832
Language : En, Es, Fr & De

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Book Description :

As technology continues to advance, it is critical for businesses to implement systems that can support the transformation of data into information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business intelligence systems, invaluable knowledge is lost. However, there are currently many different models and approaches that must be explored to determine the best method of integration. Integration Challenges for Analytics, Business Intelligence, and Data Mining is a relevant academic book that provides empirical research findings on increasing the understanding of using data mining in the context of business intelligence and analytics systems. Covering topics that include big data, artificial intelligence, and decision making, this book is an ideal reference source for professionals working in the areas of data mining, business intelligence, and analytics; data scientists; IT specialists; managers; researchers; academicians; practitioners; and graduate students.

The Philosophy of Information Quality

The Philosophy of Information Quality Book
Author : Luciano Floridi,Phyllis Illari
Publisher : Springer
Release : 2014-08-01
ISBN : 3319071211
Language : En, Es, Fr & De

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Book Description :

This work fulfills the need for a conceptual and technical framework to improve understanding of Information Quality (IQ) and Information Quality standards. The meaning and practical implementation of IQ are addressed, as it is relevant to any field where there is a need to handle data and issues such as accessibility, accuracy, completeness, currency, integrity, reliability, timeliness, usability, the role of metrics and so forth are all a part of Information Quality. In order to support the cross-fertilization of theory and practice, the latest research is presented in this book. The perspectives of experts from beyond the origins of IQ in computer science are included: library and information science practitioners and academics, philosophers of information, of engineering and technology, and of science are all contributors to this volume. The chapters in this volume are based on the work of a collaborative research project involving the Arts and Humanities Research Council and Google and led by Professor Luciano Floridi, University of Oxford. This work will be of interest to anyone handling data, including those from commercial, public, governmental and academic organizations. The expert editors’ contributions introduce issues of interest to scientists, database curators and philosophers, even though the issues may be disguised in the language and examples common to a different discipline.

Data Quality

Data Quality Book
Author : Jack E. Olson
Publisher : Elsevier
Release : 2003-01-09
ISBN : 9780080503691
Language : En, Es, Fr & De

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Book Description :

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.

Data Stewardship

Data Stewardship Book
Author : David Plotkin
Publisher : Academic Press
Release : 2020-10-31
ISBN : 0128221674
Language : En, Es, Fr & De

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Book Description :

Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality. Since the publication of the first edition, there have been critical new developments in the field, such as integrating Data Stewardship into project management, handling Data Stewardship in large international companies, handling "big data" and Data Lakes, and a pivot in the overall thinking around the best way to align data stewardship to the data—moving from business/organizational function to data domain. Furthermore, the role of process in data stewardship is now recognized as key and needed to be covered. Data Stewardship, Second Edition provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on organizational/company structure, business functions, and data ownership. The book shows data managers how to gain support for a stewardship effort, maintain that support over the long-term, and measure the success of the data stewardship effort. It includes detailed lists of responsibilities for each type of data steward and strategies to help the Data Governance Program Office work effectively with the data stewards. Includes an enhanced section on data governance/stewardship structure for companies that do business internationally, including the structure of business terms to account for country differences Outlines the advantages and disadvantages of "data domains," details on suggested data domains and data domain structures, as well as data governance by data domains Integrates data governance into Project methodology, defining roles on a project, adding Data Governance tasks to the Work Breakdown Structure, as well as advantages of working closely with the Project management Office Covers the data stewardship involved in implementing national and international data privacy regulations

Relational Database Design and Implementation

Relational Database Design and Implementation Book
Author : Jan L. Harrington
Publisher : Morgan Kaufmann
Release : 2016-04-15
ISBN : 0128499028
Language : En, Es, Fr & De

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Book Description :

Relational Database Design and Implementation: Clearly Explained, Fourth Edition, provides the conceptual and practical information necessary to develop a database design and management scheme that ensures data accuracy and user satisfaction while optimizing performance. Database systems underlie the large majority of business information systems. Most of those in use today are based on the relational data model, a way of representing data and data relationships using only two-dimensional tables. This book covers relational database theory as well as providing a solid introduction to SQL, the international standard for the relational database data manipulation language. The book begins by reviewing basic concepts of databases and database design, then turns to creating, populating, and retrieving data using SQL. Topics such as the relational data model, normalization, data entities, and Codd's Rules (and why they are important) are covered clearly and concisely. In addition, the book looks at the impact of big data on relational databases and the option of using NoSQL databases for that purpose. Features updated and expanded coverage of SQL and new material on big data, cloud computing, and object-relational databases Presents design approaches that ensure data accuracy and consistency and help boost performance Includes three case studies, each illustrating a different database design challenge Reviews the basic concepts of databases and database design, then turns to creating, populating, and retrieving data using SQL

Ethical Data and Information Management

Ethical Data and Information Management Book
Author : Katherine O'Keefe,Daragh O Brien
Publisher : Kogan Page Publishers
Release : 2018-05-03
ISBN : 0749482052
Language : En, Es, Fr & De

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Book Description :

Information and how we manage, process and govern it is becoming increasingly important as organizations ride the wave of the big data revolution. Ethical Data and Information Management offers a practical guide for people in organizations who are tasked with implementing information management projects. It sets out, in a clear and structured way, the fundamentals of ethics, and provides practical and pragmatic methods for organizations to embed ethical principles and practices into their management and governance of information. Written by global experts in the field, Ethical Data and Information Management is an important book addressing a topic high on the information management agenda. Key coverage includes how to build ethical checks and balances into data governance decision making; using quality management methods to assess and evaluate the ethical nature of processing during design; change methods to communicate ethical values; how to avoid common problems that affect ethical action; and how to make the business case for ethical behaviours.

Handbook of Research on Global Supply Chain Management

Handbook of Research on Global Supply Chain Management Book
Author : Christiansen, Bryan
Publisher : IGI Global
Release : 2015-11-12
ISBN : 1466696400
Language : En, Es, Fr & De

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Book Description :

Supply Chain Management (SCM) has always been an important aspect of an enterprise’s business model and an effective supply chain network is essential to remaining competitive in a global environment. By properly managing the flow of goods and services, businesses can operate more efficiently while managing most of the workload behind-the-scenes. The Handbook of Research on Global Supply Chain Management is an in-depth reference source that covers emerging issues and relevant applications of information pertaining to supply chain management from an international perspective. Featuring coverage on topics such as the global importance of SCMs to strategies for producing an effective supply chain, this comprehensive publication is an essential resource for academics and business professionals alike interested in uncovering managerial insight and logistics solutions.

Navigating the Labyrinth

Navigating the Labyrinth Book
Author : Laura Sebastian-Coleman
Publisher : Technics Publications
Release : 2018-05-09
ISBN : 1634623770
Language : En, Es, Fr & De

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Book Description :

An Executive Guide to Data Management