Data Quality Deniers and What We Learn from Them

Because organizations have so much data and improving their quality is perceived as a herculean task, it is very easy for people within an organization to want to avoid the problem altogether. Denial comes in several forms -- from straightforward refusal to acknowledge issues to scientific skepticism about addressing them. This talk will describe how to identify the types of data quality deniers and what any organization facing data quality issues can learn from them. It will also address how to get beyond denial to a place where organizations improve the quality of their data to more effectively leverage its value.

Speaker: Laura Sebastian-Coleman

Laura Sebastian-Coleman, Ph.D., Data Quality Director 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).