Course Description
In this course, students will build upon their existing knowledge of Apache Spark, Structured Streaming, and Delta Lake to unlock the full potential of the data lakehouse by utilizing the suite of tools provided by Databricks. This course places a heavy emphasis on designs favoring incremental data processing, enabling systems optimized to continuously ingest and analyze ever-growing data. By designing workloads that leverage built-in platform optimizations, data engineers can reduce the burden of code maintenance and on-call emergencies, and quickly adapt production code to new demands with minimal refactoring or downtime.
The topics in this course should be mastered prior to attempting the Databricks Certified Data Engineer Professional exam.
Advanced Data Engineering Outline
- Spark Core and reading Spark UI
- Working on the Cloud Vendors and Version Control
- Automate Production Workflows
- Delta Lake
- Delta Live Tables
- Managing Permissions
- Labs
Course Summary
| Next Public Course Dates | |
| Duration |
|
| Prerequisites |
|
| Available Formats |
|
| Audience |
|
Course Modules
Advanced Data Engineering
- Spark Core and reading Spark UI
- Working on the Cloud Vendors and Version Control
- Automate Production Workflows
- Delta Lake
- Delta Live Tables
- Managing Permissions
- Labs
Testimonials
“Without a doubt one of the best professional development courses I’ve taken. I would highly recommend.”
- Blaine Clark, KPERS
“Hands-down the best technical training I have taken! The methods of progressively building reports, adding complexity and features as time goes on, was fantastic.”
- Chris, Cirrus Aircraft
“It was a very enjoyable and informative course and we’re all looking forward to using the skills we learnt. We all agreed that the instructor was very good and was able to break down pretty complex issues to make them more understandable”
- Grahame Welch, Head of BI, UK Home Office
