T11 EDW Tutorial: Data Quality Assessment and Measurement

Time: Thursday, March 30th, 11.30am – 2:30pm Pacific Time (PST)/2:30pm – 5:30pm Eastern Time (EST)

This Enterprise Data World (EDW) Digital Tutorial can be purchased on the official conference website, but the live tutorial will occur within the DATAVERSITY Training Center. You will receive your unique login credentials and confirmation once you've registered for this paid Tutorial at: https://edw2023digital.dataversity.net/registration-welcome.cfm

Registration for this Tutorial will also give you access to all active tutorials within the same time slot.

All paid Tutorial registrations include access to the free 2-day program Tuesday-Wednesday. Please note that you will receive separate login instructions for the free program, as it will take place on a different platform than the Tutorials. See your registration confirmation for details.  

The EDW Digital Conference site can be found at: https://edw2023digital.dataversity.net/index.cfm

Tutorial Description

Experts agree that to improve Data Quality, you must be able to measure Data Quality. But determining what and how to measure is often challenging. This workshop will provide participants with a comprehensive and adaptable approach to Data Quality assessment. It will cover:

• The challenges of measuring Data Quality and how to address them.
• DQ assessment in context: Understand the goals and measurement activities and deliverables associated with an initial assessment, in-line measurement and control, and periodic reassessment of data. Review a template for capturing the results of data analysis from these processes. 
• Initial assessment: Review an approach to data profiling and initial data assessment that allows the capture of important observations about the condition of data.
• Defining DQ requirements: Learn how to define measurable characteristics of data and establish requirements for Data Quality. Review a template designed to solicit and document clear expectations related to specific dimensions of quality. 
• Using measurement for improvement: Share examples of measurements that contribute to the ongoing improvement of Data Quality.

Speaker: Laura Sebastian-Coleman

Laura Sebastian-Coleman, Ph.D., VP Data Management & Governance at Prudential, has worked in Data Quality Management since 2003. She has implemented Data Quality metrics and reporting, launched and facilitated Data Quality working groups, contributed to data consumer training programs, and led efforts to establish data standards and to manage metadata in support of Data Governance goals. Author of Navigating the Labyrinth (2018) and Measuring Data Quality for Ongoing Improvement (2013), her latest book, Meeting the Challenges of Data Quality Management, was published in February 2022. Laura was production editor for the DAMA-DMBOK2, for which she received DAMA’s award for Contributions to the Data Management Profession (2018).