Achieving Lakehouse Models with Spark 3.0 

It’s very easy to be distracted by the latest and greatest approaches with technology, but sometimes there’s a reason old approaches stand the test of time. Star Schemas & Kimball is one of those things that isn’t going anywhere, but as we move towards the “Data Lakehouse” paradigm - how appropriate is this modelling technique, and how can we harness the Delta Engine & Spark 3.0 to maximise it’s performance?
This session looks through the historical problems of attempting to build star-schemas in a lake and steps through a series of technical examples using features such as Delta file formats, Dynamic Partition Pruning and Adaptive Query Execution to tackle these problems.
About:
Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
Read more here: databricks.com...
See all the previous Summit sessions:
Connect with us:
Website: databricks.com
Facebook: / databricksinc
Twitter: / databricks
LinkedIn: / databricks
Instagram: / databricksinc Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. databricks.com...