• 1. Databricks Lakehouse Platform: Covers core concepts, architecture, cluster types, versioning, sharing, and Databricks Repos.
• 2. ELT with Apache Spark SQL and Python: Focuses on ELT processes, data extraction, transformation, and manipulation techniques.
• 3. Incremental Data Processing: Explores Delta Lake functionalities, Delta Live Tables, Auto Loader, and change data capture.
• 4. Production Pipelines: Addresses creating and managing production pipelines, including task management, scheduling, and error handling.
• 5. Data Governance: Covers data governance principles, meta stores, catalogs, Unity Catalog, and security. 

Exam details

• The exam has 45 multiple-choice questions.
• The time limit is 90 minutes.
• It is an online, proctored exam.
• Recommended experience is at least 6 months of hands-on data engineering on the Databricks platform.
• The certification is valid for two years. 

Related training

• Databricks offers instructor-led and self-paced training for the Databricks Certified Data Engineer Associate Exam.
• Other online platforms also provide courses for preparation, such as Udemy and Pluralsight. 

Prerequisites

While not mandatory, it is recommended to have:

• Basic knowledge of SQL and Python.
• Basic understanding of cloud fundamentals.
• Experience with the Databricks Lakehouse Platform.
• Understanding of big data concepts, including the 5 Vs.