Databricks Certified Data Engineer Professional -Preparation
Preparation course for Databricks Data Engineer Professional certification exam with hands-on training
Created by Derar Alhussein | 3 hours on-demand video course
If you are interested in becoming a Certified Data Engineer Professional from Databricks, you have come to the right place! I am here to helping you with preparing for this certification exam. By the end of this course, you should be able to:
Model data management solutions, including: Lakehouse (bronze/silver/gold architecture, tables, views, and the physical layout), General data modeling concepts (constraints, lookup tables, slowly changing dimensions)
Build data processing pipelines using the Spark and Delta Lake APIs, including: Building batch-processed ETL pipelines, Building incrementally processed ETL pipelines, Deduplicating data, Using Change Data Capture (CDC) to propagate changes,Optimizing workloads.
Understand how to use and the benefits of using the Databricks platform and its tools, including: Databricks CLI (deploying notebook-based workflows), Databricks REST API (configure and trigger production pipelines)
Build production pipelines using best practices around security and governance, including: Managing clusters and jobs permissions with ACLs, Creating row- and column-oriented dynamic views to control user/group access, Securely delete data as requested according to GDPR & CCPA
Configure alerting and storage to monitor and log production jobs, including: Recording logged metrics, Debugging errors.
Follow best practices for managing, testing and deploying code, including: Relative imports, Scheduling Jobs, Orchestration Jobs. With the knowledge you gain during this course, you will be ready to take the certification exam.
What you’ll learn
- Learn how to model data management solutions on Databricks Lakehouse
- Build data processing pipelines using the Spark and Delta Lake APIs
- Understand how to use and the benefits of using the Databricks platform and its tools
- Build production pipelines using best practices around security and governance
- Learn how to monitor and log production jobs
- Follow best practices for deploying code on Databricks