Meeting the Challenges of Data Quality Management - Brossura

Sebastian-coleman, Laura

Brossura

ISBN 10: 0128217375 ISBN 13: 9780128217375

Casa editrice: Academic Pr, 2022

Riassunto

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.

Su questo libro

Informazioni sull?autore

Laura Sebastian-Coleman, Data Quality Director at Prudential, has been a data quality practitioner since 2003. She has implemented data quality metrics and reporting, launched and facilitated working stewardship groups, contributed to data consumer training programs, and led efforts to establish data standards and manage metadata. In 2009, she led a group of analysts in developing the Data Quality Assessment Framework (DQAF), which is the basis for her 2013 book, Measuring Data Quality for Ongoing Improvement. An active professional, Laura has delivered papers, tutorials, and keynotes at data-focused conferences, such as MIT’s Information Quality Program, Data Governance and Information Quality (DGIQ), Enterprise Data World (EDW), Data Modeling Zone, and Data Management Association (DAMA)-sponsored events. From 2009 to 2010, she served as IAIDQ’s Director of Member Services. In 2015, she received the IAIDQ Distinguished Member Award. DAMA Publications Officer (2015 to 2018) and production editor for the DAMA-DMBOK2 (2017), she is also author of Navigating the Labyrinth: An Executive Guide to Data Management (2018). In 2018, she received the DAMA award for excellence in the data management profession. She holds a CDMP (Certified Data Management Professional) from DAMA, an IQCP (Information Quality Certified Professional) from IAIDQ, a Certificate in Information Quality from MIT, a B.A. in English and History from Franklin & Marshall College, and a Ph.D. in English Literature from the University of Rochester.

Dalla quarta di copertina

Meeting the Challenges of Data Quality Management 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 an asset). Organizations that fail to meet these challenges get less value from their data than organizations that address them directly.

Key Features:

Describes the importance of high-quality data to organizations wanting to leverage their data 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

Provides Data Quality practitioners with ways to communicate consistently with stakeholders

"If you are concerned about poor-quality, untrustworthy data and its impact on your organization (and the world), then Laura Sebastian-Coleman’s latest book, Meeting the Challenges of Data Quality Management, is for you. Readers will appreciate her ability to think deeply about the problems, combine research with her years of experience, and come to well-thought-out conclusions. She clearly expresses the challenges and solutions in a way that speaks to those who create and manage data, as well as to those leaders who are promoting better use of data to help their organizations. Read it, use it, share it!"

—Danette McGilvray

, President, Granite Falls Consulting, Clinton, UT, USA, and Author of Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ (2nd Edition)

"Laura Sebastian-Coleman recognizes that data is a representation of the activities of an organization and that to improve the business’ data quality is also to improve the organization, its people and technology as such. Those who might claim that a Data Governance program, or AI, or a better system, or coercive management, or other quick fixes will "straighten out our data" suffer from a lack of insight, insight that this book describes. This book is a must read for anyone attempting data quality improvement. Laura provides the fundamental and in-depth knowledge needed to accomplish changes that work and last; this is the improvement hiker’s comprehensible guide to the data galaxy."

—Håkan Edvinsson, Author, consultant, and founder of the Diplomatic Data Governance concept, Helsingborg, Sweden

"Dr. Sebastian-Coleman’s new book is a great sequel to her first book, Measuring Data Quality for Ongoing Improvement. Our Information Quality Graduate Program has been using MDQOI as a standard textbook for the program’s Principles of Information Quality course since its publication in 2013. While the first book provides a very clear and effective guide for "how" to systematically measure data quality, her new book expands this perspective to include the broader context of "why" an organization should incorporate data quality management best practices into its strategic plan. It provides a clear roadmap for bringing together data, processes, technology, and people into systems that maximize the value of an organization’s data assets. It also describes how data quality management practices must be adapted to meet the challenges of big data, data literacy, data governance, and data protection. I highly recommend this book for any organization trying to build and improve its data strategy, and as a textbook for data management, data science, and information science programs."

—John R. Talburt

, PhD, IQCP, CDMP, Acxiom Chair of Information Quality, University of Arkansas at Little Rock, and Lead Consultant for Data Quality and Data Governance, Noetic Partners, Little Rock, AK, USA

Dettagli dell'edizione

• Editore: Academic Pr
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 0128217375
• ISBN 13: 9780128217375
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 315
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile