Best of Spark + AI Summit 2020
The recent Spark + AI Summit attracted nearly 70K registrants and incredible speakers, such as Nate Silver, Dr. Phillip Atiba Goff, Hany Farid, Jennifer Chayes, Adam Paszke, as well as Databricks leaders. Watch on-demand exciting keynotes from industry leaders, including Starbucks on how they transformed their on-prem infrastructure to cloud-plus-AI, as well as 200+ breakout sessions, now available online.
For referenceability, here is a curated list of top sessions by discipline and by industry: Data Science, Data Engineering, Public Sector, Media and Entertainment, Health and Life Sciences, Financial Services and Retail and CPG.
We received over 50 submissions for this hackathon launched in May to see what solutions data teams could devise around the COVID-19 crisis, climate change and social issues in their communities. Congratulations to all our winners!
Second Runner Up: Booz Allen Hamilton, Climate Resiliency for the Chesapeake Bay, $5000 donation to the Alliance for the Chesapeake Bay on their behalf.
Runner Up: Shell and Enbridge, Wildfire Real-time Detection using Satellite Imagery, $10,000 to the Amazon Conservation Association on their behalf.
Grand Prize Winner: Revgen, Taking it to the Streets, $20,000 to The Gathering Place on their behalf.
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Best Practices and Demos
Cost cutting has become a paramount concern. We developed a program to demonstrate how much more cost effective and performant it would be to shift from EMR to Databricks, while still maintaining all data on AWS. The Production Pipelines Program includes preferential pricing, compute credits, a funded PoC, and a deep cost and performance evaluation report. Watch this webinar to learn more about the program, how to qualify, and how other Databricks customers have cut costs and improved performance of their production pipelines.
Uncover the most impactful techniques you can implement for a new data governance strategy. This guide demonstrates a typical deployment workflow you can employ using Databricks and cloud-native solutions to secure and monitor each layer from the application down to storage.
Learn to keep track of both historical and current data over time with Slowly Changing Dimensions, a fundamental concept from the data warehousing world. This talk discusses how to apply these concepts to your data lake.
Learn to manage and scale machine learning models for IoT devices with Model Training and Model Scoring.
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