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Tackling data quality issues, 5 pillars of data observability, from management consultant to CEO of Monte Carlo - Barr Moses -The Data Scientist Show #062
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.Barr's LinkedIn: https://www.linkedin.com/in/barrmoses/Daliana's Twitter: https://twitter.com/DalianaLiuDaliana's LinkedIn: https://www.linkedin.com/in/dalianaliu
(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
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By Daliana Liu
4.7
7575 ratings
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.Barr's LinkedIn: https://www.linkedin.com/in/barrmoses/Daliana's Twitter: https://twitter.com/DalianaLiuDaliana's LinkedIn: https://www.linkedin.com/in/dalianaliu
(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
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