Measuring Data Quality for Ongoing Improvement by Laura Sebastian-Coleman
Shows you how to measure and monitor data quality, ensuring quality over time. This title demonstrates how to leverage a technology independent data quality measurement framework for specific business priorities and data quality challenges. It enables discussions between business and IT with a non-technical vocabulary for data quality measurement.
"This book provides a very well-structured introduction to the fundamental issue of data quality, making it a very useful tool for managers, practitioners, analysts, software developers, and systems engineersIt also helps explain what data quality management entails and provides practical approaches aimed at actual implementation. I positively recommend reading it…" --ComputingReviews.com, January 2014 "The framework she describes is a set of 48 generic measurement types based on five dimensions of data quality: completeness, timeliness, validity, consistency, and integrity. The material is for people who are charged with improving, monitoring, or ensuring data quality." --Reference and Research Book News, August 2013 "If you are intent on improving the quality of the data at your organization you would do well to read Measuring Data Quality for Ongoing Improvement and adopt the DQAF offered up in this fine book." --Data and Technology Today blog, July 2013
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.
| SKU | Unavailable |
| ISBN 13 | 9780123970336 |
| ISBN 10 | 0123970334 |
| Title | Measuring Data Quality for Ongoing Improvement |
| Author | Laura Sebastian-Coleman |
| Series | The Morgan Kaufmann Series On Business Intelligence |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Elsevier Science & Technology |
| Year published | 2013-02-20 |
| Number of pages | 376 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |