In May, Databricks hosted an introductory course on Databricks Data Engineering.  

This course offered firsthand training on the components of the Databricks Lakehouse Platform. Attendees leveraged structured query language (SQL) and Python to define and schedule pipelines that incrementally process new data from a variety of data sources which power analytic applications and dashboards in the Lakehouse. 

Attendees learned how to:

• Leverage the Databricks Lakehouse Platform to perform core responsibilities for data pipeline development
• Use SQL and Python to write production data pipelines to manage data into tables and views in the Lakehouse
• Orchestrate production pipelines to deliver fresh results for ad-hoc analytics and dash-boarding
• Simplify data ingestion and incremental change propagation using Databricks-native features and syntax, including Delta Live Tables 

Interested in learning more? Fill out the form to discover how you can engage with Databricks to accomplish training in data engineering