Data Brew by Databricks

For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.
Winner of the infamous Last Man Standing race (running 246 miles in 59 hours), Guillaume merges the world of competitive long-distance running with data science to push the boundaries of body and mind.
See more at databricks.com/data-brew

For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.
Alexander Powell chronicles the evolution of sports analytics and how professional sports teams use data as a competitive advantage.
See more at databricks.com/data-brew

For our fourth season, we focus on connected health and how data & AI augment and improve our daily health. While we’re at it, we’ll be enjoying our morning brew.
Globally, 38,000 people get hurt on the job every hour. In the United States alone, over $250 billion dollars is spent on workplace injury annually. Sean Petterson, founder and CEO of StrongArm Tech, discusses the role of wearable devices to reduce workplace injury and increase retention of industrial athletes.
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For our third season, we focus on how leaders use data for change. Whether it’s building data teams or using data as a constructive catalyst, we interview subject matter experts from industry to dive deeper into these topics.
For our season 3 finale, Nithya Ruff discusses the open-source ecosystem, ways to contribute to open-source projects (hint: it’s not just about the code), and how businesses can balance community and company interests. With 95% of open-source contributions coming from men, Nithya also educates us on how to improve diversity & inclusion in the open-source community.

See more at databricks.com/data-brew

Our fifth season dives into large language models (LLMs), from understanding the internals to the risks of using them and everything in between. While we're at it, we'll be enjoying our morning brew.
In this session, we interviewed Chengyin Eng (Senior Data Scientist, Databricks), Sam Raymond (Senior Data Scientist, Databricks), and Joseph Bradley (Lead Production Specialist - ML, Databricks) on the best practices around LLM use cases, prompt engineering, and how to adapt MLOps for LLMs (i.e., LLMOps).