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AI comes to the rescue of the data team: How to use data learning to reduce data cloud costs

Date/Time: On Demand

As the cloud continues to expand at an exponential rate, organizations face challenges presented by increasing users and apps, growing expert and infra costs, and overall, more complexity. While data clouds lower the CapEx barrier, they also greatly increase the OpEx barrier.

Join us for this informative workshop based on research published in SIGMOD, which since 1975 has been among the most important data industry conferences. You'll learn how data learning can enable you to lower costs, reduce ops burden, and improve performance, while automating and accelerating many use cases. 

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What you’ll learn

1
How to utilize automated data warehouse optimization to alleviate soaring costs and overwhelmed data teams
2
The design criteria, architecture, and smart models behind Keebo’s automated warehouse optimization

3
Deep insights into data learning and the results it can provide at the warehouse, schema, and query level, including performance telemetry, memory optimization, and deep reinforcement learning

About the presenter

Barzan 300x300

Barzan Mozafari, PhD, Keebo

Prof. Barzan Mozafari, co-founder and CEO of Keebo, and leading academic, has spent the last decade and a half of his career conducting award-winning research at the intersection of Machine Learning and Database Systems across various institutions, including University of Michigan, MIT, UCLA as well as several startups.

About Keebo: 
Fully automated Snowflake optimization

Our robots never stop working–and you only pay a percentage of the savings.

fully-automated

Fully automated
Optimizes Snowflake automatically in real time

fast

Fast
No changes to your system, results in 24-48 hours

friendly

Friendly
Never accesses user data; adjustable and customizable

Watch a brief introduction to Keebo