talk-data.com
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Delta Lake
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Databricks co-founders created Spark, the wildly popular open source foundation of Databricks, way back in 2009. Learn from Michael Armbrust, creator of Spark SQL and leader of Databricks Delta, about the latest happenings in Spark, Lakeflow Declarative Pipelines, and open source.
Join Databricks' Distinguished Principal Engineer Michael Armbrust for a technical deep dive into how Delta Live Tables (DLT) reduces the complexity of data transformation and ETL. Learn what’s new; what’s coming; and how to easily master the ins-and-outs of DLT.
Michael will describe and demonstrate:
Talk by: Michael Armbrust
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Day 1 Morning Keynote | Data + AI Summit 2022 Welcome & "Destination Lakehouse" | Ali Ghodsi Apache Spark Community Update | Reynold Xin Streaming Lakehouse | Karthik Ramasamy Delta Lake | Michael Armbrust How Adobe migrated to a unified and open data Lakehouse to deliver personalization at unprecedented scale | Dave Weinstein Data Governance and Sharing on Lakehouse |Matei Zaharia Analytics Engineering and the Great Convergence | Tristan Handy Data Warehousing | Shant Hovespian Unlocking the power of data, AI & analytics: Amgen’s journey to the Lakehouse | Kerby Johnson
Get insights on how to launch a successful lakehouse architecture in Rise of the Data Lakehouse by Bill Inmon, the father of the data warehouse. Download the ebook: https://dbricks.co/3ER9Y0K
Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/
Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/
Day 2 Morning Keynote | Data + AI Summit 2022 Production Machine Learning | Patrick Wendell MLflow 2.0 | Kasey Uhlenhuth Revolutionizing agriculture with AI: Delivering smart industrial solutions built upon a Lakehouse architecture | Ganesh Jayaram Intuit’s Data Journey to the Lakehouse: Developing Smart, Personalized Financial Products for 100M+ Consumers & Small Businesses | Alon Amit and Manish Amde Workflows | Stacy Kerkela Delta Live Tables | Michael Armbrust AI and creativity, and building data products where there's no quantitative metric for success, such as in games, or web-scale search, or content discovery | Hilary Mason What to Know about Data Science and Machine Learning in 2022 | Peter Norvig Data-centric AI development: From Big Data to Good Data | Andrew Ng
Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/
Data + AI Summit Keynote talk from Michael Armbrust
Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/
Summary Building and maintaining a data lake is a choose your own adventure of tools, services, and evolving best practices. The flexibility and freedom that data lakes provide allows for generating significant value, but it can also lead to anti-patterns and inconsistent quality in your analytics. Delta Lake is an open source, opinionated framework built on top of Spark for interacting with and maintaining data lake platforms that incorporates the lessons learned at DataBricks from countless customer use cases. In this episode Michael Armbrust, the lead architect of Delta Lake, explains how the project is designed, how you can use it for building a maintainable data lake, and some useful patterns for progressively refining the data in your lake. This conversation was useful for getting a better idea of the challenges that exist in large scale data analytics, and the current state of the tradeoffs between data lakes and data warehouses in the cloud.
Announcements
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Interview
Introduction How did you get involved in the area of data m