A Guide to Data Engineering using Databricks

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Presented by

Sam Harley, Solutions Architect, Databricks Australia & New Zealand

About this talk

The rise of the lakehouse architectural pattern is built upon tech innovations enabling the data lake to support ACID transactions and other features of traditional data warehouse workloads. Join this session for a walkthrough of the Databricks Lakehouse architecture for Data Engineering. Learning outcomes: - How Databricks Lakehouse combines the reliability, performance and governance of data warehouses with the openness and flexibility of data lakes - Technology foundations of Delta Lake (Apache Spark™) and Databricks SQL - How to build highly scalable data pipelines and tackling merged streaming and batch workloads - Powering data science with Delta Lake and MLflow

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No matter at what stage of your data journey you’re in, this channel will help you get a better understanding of the fundamental concepts of the Databricks Lakehouse platform and the problems we’re helping to solve for data teams.