Data Brew
Let’s talk data

Welcome to Data Brew by Databricks with Denny and Brooke!

In this series, we explore various topics in the data and AI community and interview experts in data engineering and data science. So join us with your morning brew in hand and get ready to dive deep into data and AI.


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Season 1

For this first season, we will be focusing on data lakehouses – combining the key features of data warehouses, such as ACID transactions, with the scalability of data lakes, directly against low-cost object stores.

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Miss Season 1?

You can still catch Season 1 on Data Lakehouses here, on YouTube, and on your favorite podcast service like Spotify and Apple Music.


From data warehousing to data lakes in 40 minutes

Join this panel of data warehousing luminaries of Barry Devlin, Susan O’Connell, and Donald Farmer to discuss the evolution of data warehouses, data lakes, and data lakehouses.

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Welcome to Lakehouse

Join Ali Ghodsi, CEO and co-founder of Databricks, and David Meyer, SVP of Product at Databricks, for a detailed tour of the Data Lakehouse architecture.

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Demystifying Delta Lake

Join Michael Armbrust, Spark PMC Member and Engineering Lead for Structured Streaming & Delta Lake at Databricks, to explore the journey building data lake technology.

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BI on Data Lakes – Making it Real for Retail

Lara Minor, Senior Enterprise Data Manager at Columbia Sportswear, discusses how her team achieved a 70% reduction in pipeline creation time. This reduced ETL workload times from four hours with previous data warehouses to minutes using Azure Databricks, hence enabling near real-time analytics.

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Combining Machine Learning and MLflow with your Data Lakehouse

Ellissa Verseput, ML Engineer at Quby, joins Denny and Brooke to discuss how Quby leverages ML to extract additional value from their data lake and how they manage this process.

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Journey of Big Data

Jules Damji and Tathagata Das guide us through their journey in big data and the evolution of data architecture in the past 30 years. They discuss some of the biggest changes in industry they’ve seen, as well as trends to look forward to in the coming years. This is a fun episode connecting all four authors of the Learning Spark, 2nd Edition book.

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About the hosts

Brooke Wenig

Brooke Wenig is a Director of the Machine Learning Practice at Databricks. She leads a team of data scientists who develop large-scale machine learning pipelines for customers, as well as teach courses on distributed machine learning best practices. Previously, she was a Principal Data Science Consultant at Databricks. She received an M.S. in Computer Science from UCLA with a focus on distributed machine learning. She speaks Mandarin Chinese fluently and enjoys cycling.

Denny Lee

Denny Lee is a Developer Advocate at Databricks. He is a hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale infrastructure, data platforms, and predictive analytics systems for both on-premises and cloud environments. He has a Master’s of Biomedical Informatics from Oregon Health and Sciences University and has architected and implemented powerful data solutions for enterprise healthcare customers. His current technical focuses include distributed systems, Apache Spark, deep learning, machine learning and genomics.

Brooke and Denny are two of the co-authors of Learning Spark, 2nd edition.

Contact the Data Brew team on Twitter: @databrew_db or on LinkedIn