Barr Moses is a consultant turned CEO & Co-Founder of Monte Carlo, a data reliability company. She started her career as a management consultant at Bain & Company and a research assistant at the Statistics Department at Stanford University. Later, she became VP of Customer Operations at customer success company Gainsight, where she built the data and analytics team. 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. Today, we’ll talk about Barr’s career journey, data reliability and observability, and what it means for data teams. If you enjoy the show, subscribe to the channel and leave a 5-star review. Subscribe to Daliana's newsletter on www.dalianaliu.com for more on data science.
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00:00:00 Introduction
00:01:24 How did she got into data science
00:08:26 Frameworks for data-driven decisions
00:11:20 Is customer support ticket always bad?
00:15:20 How to quickly find out what is true
00:20:17 Struggles in the data team
00:23:37 Daliana’s story about lineage
00:28:00 People stressed about data
00:28:09 Netflix was down because of wrong data
00:30:40 Common issues with data quality
00:33:14 5 pillars of data observability
00:39:14 How does Monte Carlo help data scientists
00:43:08 Build in-house vs adopt tools
00:45:48 How Daliana fixed a data quality issue
01:02:44 How to measure the impact of the data team
01:09:09 Mistakes she made
01:15:28 Beat the odds
