Coffee Sessions #19 with Barr Moses of Monte Carlo, Introducing Data Downtime: How to Prevent Broken Data Pipelines with Observability, co-hosted by Vishnu Rachakonda.

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// Bio
Barr Moses is CEO & Co-Founder of Monte Carlo, a data observability company backed by Accel 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. 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.

// Talk Takeaways
As companies become increasingly data-driven, the technologies underlying these rich insights have grown more and more nuanced and complex. While our ability to collect, store, aggregate, and visualize this data has largely kept up with the needs of modern data teams (think: domain-oriented data meshes, cloud warehouses, data visualization tools, and data modeling solutions), the mechanics behind data quality and integrity have lagged.

To keep pace with data’s clock speed of innovation, data engineers need to invest not only in the latest modeling and analytics tools but also in technologies that can increase data accuracy and prevent broken pipelines. The solution? Data observability, the next frontier of data engineering and a pillar of the emerging Data Reliability category, and the fix for eliminating data downtime.

During this talk, listeners will learn about:

• The rise (and threat) of data downtime
• The relationship between DevOps Observability and Data Observability
• Data Observability and its five key pillars
• How the best data teams are leveraging Data Observability to prevent broken pipelines

// About Monte Carlo

As businesses increasingly rely on data to drive better decision-making, it’s mission-critical that this data is accurate and reliable. Billed by Forbes as the New Relic for data teams and backed by Accel and GGV, Monte Carlo solves the costly problem of broken data through their fully automated, end-to-end data reliability platform. Data teams spend north of 30% of their time tackling data quality issues, distracting data engineers, data scientists, and data analysts from working on revenue-generating projects. Providing full coverage of your data stack – all the way from data lake and warehouse to analytics dashboard – Monte Carlo’s platform empowers companies such as Eventbrite, Compass, Vimeo, and other enterprises to trust their data, saving time and money and unlocking the potential of data.

// Other links you can check Barr on
Learn more about Monte Carlo: https://www.montecarlodata.com
What is data downtime? https://www.montecarlodata.com/the-rise-of-data-downtime/  
What is data observability? https://www.montecarlodata.com/data-observability-the-next-frontier-of-data-engineering/
How data observability prevents broken data pipelines: https://www.montecarlodata.com/data-observability-how-to-prevent-your-data-pipelines-from-breaking/