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How to Eliminate Data Downtime & Start Trusting Your Data

Posted Apr 22
# Spring Summit - 2022
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SPEAKER
Barr Moses
Barr Moses
Barr Moses
CEO and Co-Founder @ Monte Carlo

Barr Moses is CEO & Co-Founder of Monte Carlo, a data reliability company and creator of the industry’s first Data Observability Platform, backed by Accel, GGV, Redpoint, ICONIQ Growth, Salesforce Ventures, 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. She is a co-author of O’Reilly first-ever book on data quality and observability, Data Quality Fundamentals: Building Trustworthy Data Pipelines (coming September 2022).

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Barr Moses is CEO & Co-Founder of Monte Carlo, a data reliability company and creator of the industry’s first Data Observability Platform, backed by Accel, GGV, Redpoint, ICONIQ Growth, Salesforce Ventures, 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. She is a co-author of O’Reilly first-ever book on data quality and observability, Data Quality Fundamentals: Building Trustworthy Data Pipelines (coming September 2022).

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SUMMARY

Broken data is costly, time-consuming, and nowadays, an all-too-common reality for even the most advanced data teams. In this talk, I’ll introduce this problem, called “data downtime” — periods of time when data is partial, erroneous, missing or otherwise inaccurate — and discuss how to eliminate it in your data ecosystem with end-to-end data observability. Drawing corollaries to application observability in software engineering, data observability is a critical component of the modern DataOps workflow and the key to ensuring data trust at scale. I’ll share why data observability matters when it comes to building a better data quality strategy and highlight tactics you can use to address it today.

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