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Broken data is costly, time-consuming, and nowadays, an all-too-common reality for even the most advanced data teams. In this talk, we will 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. We will 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.

Jon So DSS

Jon So, Head of Product Marketing at Monte Carlo

Jon So leads product and partner marketing at Monte Carlo. Prior to Monte Carlo, Jon led product marketing, pricing strategy, and growth teams at Twilio Segment, Nauto, and Oracle | Opower, and advised Fortune 500 companies while working in Deloitte Consulting’s Strategy & Operations practice. He resides in San Francisco, CA, and graduated from the University of North Carolina at Chapel Hill.

katienoonan

Katie Noonan, Support Engineer at Monte Carlo

Katie Noonan leads the technical support department at Monte Carlo. Prior to Monte Carlo, Katie specialized in technical enablement for enterprise accounts, and product process and operations at Twilio Segment. She currently resides in San Francisco, CA, and graduated from the University of Oregon.

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