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Databricks Data Engineer Associate Study Guide

Domain-by-domain study guide for Databricks Certified Data Engineer Associate (Databricks-DE-Associate). Covers all 5 exam objectives with topic checklists, quick notes, and practice links.

Download PDF Notes

Exam Overview

Key facts before you start studying

Duration

90 min

Questions

Exam Code

Databricks-DE-Associate

Domains

Quick Navigation

Jump to a specific exam domain

1. Databricks Lakehouse Platform (24%)
2. ELT with Spark SQL and Python (29%)
3. Incremental Data Processing (22%)
4. Production Pipelines (16%)
5. Data Governance (9%)

Domain 1

24%

Databricks Lakehouse Platform

Understand the Databricks Lakehouse Platform architecture, components, and capabilities

Topics to Master

Data lakehouse concepts and architecture
Databricks workspace and notebooks
Databricks clusters and compute resources
Unity Catalog for data governance
Delta Lake storage layer
Databricks File System (DBFS)
Databricks SQL and SQL warehouses
Data Explorer and catalog browser
Workspace administration and access control

Domain 2

29%

ELT with Spark SQL and Python

Extract, Load, and Transform data using Spark SQL and Python

Topics to Master

Extracting data from external sources
Loading data into Delta Lake tables
Using Spark SQL for data transformation
PySpark DataFrame API operations
Working with structured and semi-structured data
Data quality validation and testing
Writing efficient Spark queries
Handling schema evolution
Optimizing query performance

Domain 3

22%

Incremental Data Processing

Process data incrementally using Delta Live Tables, Structured Streaming, and Auto Loader

Topics to Master

Delta Live Tables pipelines
Structured Streaming fundamentals
Auto Loader for incremental file ingestion
Watermarking and windowing operations
Change Data Capture (CDC) patterns
Managing streaming state
Handling late-arriving data
Checkpointing and fault tolerance
Monitoring streaming queries

Domain 4

16%

Production Pipelines

Build and manage production data pipelines with orchestration and monitoring

Topics to Master

Databricks Jobs for pipeline orchestration
Task dependencies and scheduling
Multi-task workflows
Job monitoring and alerting
Error handling and retry logic
Pipeline optimization techniques
Version control and CI/CD integration
Performance tuning for production
Resource management and cost optimization

Domain 5

Data Governance

Implement data governance, security, and privacy controls

Topics to Master

Unity Catalog security model
Table and column-level access control
Dynamic view functions for row/column filtering
Data lineage tracking
Audit logging and compliance
Data masking and encryption
GDPR and data privacy requirements
Retention policies and data lifecycle
Sharing data securely across workspaces

Continue Your Prep

Free CertStud resources for Databricks-DE-Associate

Study Notes Exam Study Plan Start Practice Test

Back to Databricks Data Engineer Associate

Databricks Data Engineer Associate Study Guide

Domain-by-domain study guide for Databricks Certified Data Engineer Associate (Databricks-DE-Associate). Covers all 5 exam objectives with topic checklists, quick notes, and practice links.

Download PDF Notes

Exam Overview

Key facts before you start studying

Duration

90 min

Questions

Exam Code

Databricks-DE-Associate

Domains

Quick Navigation

Jump to a specific exam domain

1. Databricks Lakehouse Platform (24%)
2. ELT with Spark SQL and Python (29%)
3. Incremental Data Processing (22%)
4. Production Pipelines (16%)
5. Data Governance (9%)

Domain 1

24%

Databricks Lakehouse Platform

Understand the Databricks Lakehouse Platform architecture, components, and capabilities

Topics to Master

Data lakehouse concepts and architecture
Databricks workspace and notebooks
Databricks clusters and compute resources
Unity Catalog for data governance
Delta Lake storage layer
Databricks File System (DBFS)
Databricks SQL and SQL warehouses
Data Explorer and catalog browser
Workspace administration and access control

Domain 2

29%

ELT with Spark SQL and Python

Extract, Load, and Transform data using Spark SQL and Python

Topics to Master

Extracting data from external sources
Loading data into Delta Lake tables
Using Spark SQL for data transformation
PySpark DataFrame API operations
Working with structured and semi-structured data
Data quality validation and testing
Writing efficient Spark queries
Handling schema evolution
Optimizing query performance

Domain 3

22%

Incremental Data Processing

Process data incrementally using Delta Live Tables, Structured Streaming, and Auto Loader

Topics to Master

Delta Live Tables pipelines
Structured Streaming fundamentals
Auto Loader for incremental file ingestion
Watermarking and windowing operations
Change Data Capture (CDC) patterns
Managing streaming state
Handling late-arriving data
Checkpointing and fault tolerance
Monitoring streaming queries

Domain 4

16%

Production Pipelines

Build and manage production data pipelines with orchestration and monitoring

Topics to Master

Databricks Jobs for pipeline orchestration
Task dependencies and scheduling
Multi-task workflows
Job monitoring and alerting
Error handling and retry logic
Pipeline optimization techniques
Version control and CI/CD integration
Performance tuning for production
Resource management and cost optimization

Domain 5

Data Governance

Implement data governance, security, and privacy controls

Topics to Master

Unity Catalog security model
Table and column-level access control
Dynamic view functions for row/column filtering
Data lineage tracking
Audit logging and compliance
Data masking and encryption
GDPR and data privacy requirements
Retention policies and data lifecycle
Sharing data securely across workspaces

Continue Your Prep

Free CertStud resources for Databricks-DE-Associate

Study Notes Exam Study Plan Start Practice Test