Key Moments: Why is the data wrong? (6:00) Our products are our data (11:00) The true size of the data quality problem (14:00) Clean your data before you prioritize shiny new tools (26:00) The next frontier: GenAI and unstructured data (31:00) Key Quotes: “The data estate has changed significantly. But the way in which we manage data and data quality specifically has not adapted.” – Barr Moses “I tracked every single change in the data that I made, and could calculate how much money a company saved after a data cleanup. For a mid-size company, the difference was approximately a quarter of a billion dollars. For a large company, it could be several billion dollars. 45% of the data I cleaned had errors.” – Olga Maydanchik “The competitive advantage is really the access to your proprietary data that you have as an enterprise. So you need to make sure that that data is accurate, reliable, and on time. Now, how do you do that? That's something that people are still figuring out.” – Barr Moses Mentions: Information Quality Applied: Best Practices for Improving Business Information, Outcomes and Systems: Book by Larry English The Rest is History Podcast Freakonomics Podcast The Matrix Film Series The Play That Goes Wrong Bio: Barr Moses: Barr Moses is the CEO and Co-Founder of Monte Carlo, the data reliability company. Monte Carlo is the creator of the industry's first end-to-end Data Observability platform. She is also co-author of O'Reilly's Data Quality Fundamentals: Building Reliable Data Pipelines. Previously, she was VP Customer Operations at Gainsight, a management consultant at Bain & Company and served in the Israeli Air Force as a commander of an intelligence data analyst unit. Olga Maydanchik: Olga Maydanchik is a data governance, data quality, and data architecture thought leader and practitioner. She is an expert in design and implementation of enterprise-wide data management programs, who has led data quality efforts at Deutsche Bank, AIG, and at Citi. Hear more from Cindi Howson here . Sponsored by ThoughtSpot .
