As organizations of all sizes continuously look to drive value out of data, the modern data stack has emerged as a clear solution for getting insights into the hands of the organization. With the rapid pace of innovation not slowing down, the tools within the modern data stack have enabled data teams to drive faster insights, collaborate at scale, and democratize data knowledge. However, are tools just enough to drive business value with data? In the first of our four RADAR 2023 sessions, we look at the key drivers of value within the modern data stack through the minds of Yali Sassoon and Barr Moses. Yali Sassoon is the Co-Founder and Chief Strategy Officer at Snowplow Analytics, a behavioral data platform that empowers data teams to solve complex data challenges. At Snowplow, Yali gets to combine his love of building things with his fascination of the ways in which people use data to reason.Barr Moses is CEO & Co-Founder of Monte Carlo. Previously, she was VP Customer Operations at customer success company Gainsight, where she helped scale the company 10x in revenue and, among other functions, built the data/analytics team. Listen in as Yali and Barr outline how data leaders can drive value creation with data in 2023.

CEO Barr Moses, Cofounder Prukalpa Sankar, and CEO George Fraser discuss scaling data quality for generative AI. Topics include challenges in data quality and trust, cultural issues, importance of data quality in AI use cases, permissions complexity in AI applications, and impact on organizational success.

Overview Barr Moses, Co-Founder and CEO of Monte Carlo, joins on the podcast. Prior to founding Monte Carlo, Barr was the VP of customer success operations at Gainsight and holds a bachelors of science in mathematics and computer science from Stanford. In today’s episode Barr shares her inspiration for founding Monte Carlo, the cost and harms of poor quality data, the five principles of data observability, and her top predictions for data trends in 2023. About Barr Moses Barr Moses is CEO & Co-Founder of Monte Carlo, a data reliability company and creator of the data observability category, backed by Accel, GGV, Redpoint, ICONIQ Growth, Salesforce Ventures, IVP, and other top Silicon Valley investors. Previously, she was VP Customer Operations at customer success company Gainsight, where she helped scale the company 10x in revenue and, among other functions, built the data/analytics team. Prior to that, she was a management consultant at Bain & Company and a research assistant at the Statistics Department at Stanford University. She also served in the Israeli Air Force as a commander of an intelligence data analyst unit. Barr graduated from Stanford with a B.Sc. in Mathematical and Computational Science. Social Handles LinkedIn Barr's Twitter Monte Carlo's Twitter Monte Carlo's Website Learn more about our mission and become a member here: https://www.womenindata.org/ --- Support this podcast: https://podcasters.spotify.com/pod/show/women-in-data/support

Three industry experts, including Barr Moses, CEO of Monte Carlo Data, discuss scaling data quality for generative AI. They explore challenges, best practices, and governance in the age of AI. Topics include AI roles, organizational transformation, evolving AI skills, storytelling in AI, prompt engineering, and navigating the AI job market.

Barr Moses, Co-Founder and CEO of Monte Carlo, shares her inspiring journey from data strategy at Bain to building a pioneering data observability platform. She discusses her unique experiences in the Israeli Army and highlights the importance of teamwork and feedback in data science. The conversation dives into the critical need for reliable data, illustrated by a staggering $100 million loss due to a data error. Barr also explains the five pillars of data observability and emphasizes how data accuracy is vital for trust, especially in an AI-driven future.