Build a lakehouse with Delta Lake and Spark

Jonathan Neo presented this lakehouse session to the Sydney Databricks Meetup in October 2021. The talk connected Delta Lake and Spark to an end-to-end ingestion workflow.

This page is a session record. The old download form did not contain a recoverable slide or recording link, so it has been removed rather than left as a working promise.

Published session outline

• The components of a lakehouse architecture.
• How Delta Lake and Spark supported the architecture shown in the talk.
• An end-to-end data-ingestion pipeline.

Current Databricks runtimes, table-management features, and architecture guidance have changed since the event. Use the session as historical context, then check current product documentation before implementing the pattern.

Presenter record

The event listed Jonathan Neo as the presenter. His biography and job title on the original page belong to 2021 and are not repeated as current facts.

The session was hosted through the Sydney Databricks Meetup.