Search...

Quick Feedback

Databricks-DE-Associate

Databricks Data Engineer Associate Exam Guide

A 5-week study plan aligned to official Databricks-DE-Associate exam domains.

Exam Information

90 minutes

Duration

60 questions (approx.)

Questions

70%

Passing Score

See official exam pricing

Exam Cost

Recommended Study Plan

Week 1

Databricks Lakehouse Platform

24% of exam

6-8 hours

Focus: Unity Catalog is the governance layer — permissions, lineage, audit across workspaces
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#lakehouse-platform

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 2

ELT with Spark SQL & Python

29% of exam

10-12 hours

Focus: Prefer DataFrame API for complex pipelines; Spark SQL for ad-hoc analytics
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#elt-spark-sql-python

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 3

Incremental Data Processing

22% of exam

6-8 hours

Focus: CDC with MERGE INTO — match on key, update/insert/delete based on change type
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#incremental-data-processing

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 4

Production Pipelines

16% of exam

6-8 hours

Focus: Multi-task jobs replace legacy single-notebook job pattern
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#production-pipelines

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 5

Data Governance

9% of exam

6-8 hours

Focus: Row filters and column masks are Unity Catalog features — not manual views
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#data-governance

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 6

Final Review & Practice Exams

All domains

8-10 hours

Complete all three full-length practice exams
Review incorrect answers and weak domains
Revisit flashcards for key terms
Timed review of highest-weight domains

Recommended Resources:

Practice exams

Flashcards

Study notes PDF

Exam Tips & Strategies

Domain Insight 1

Unity Catalog is the governance layer — permissions, lineage, audit across workspaces

Domain Insight 2

Delta Lake provides ACID — plain Parquet on S3/ADLS does not

Follow Domain Weights

Spend more study time on higher-weighted domains — they drive the majority of exam questions.

Practice Under Time Pressure

Use timed practice exams to build pacing before test day.

Key Topics to Master

Data lakehouse concepts and architecture

Databricks workspace and notebooks

Extracting data from external sources

Loading data into Delta Lake tables

Delta Live Tables pipelines

Structured Streaming fundamentals

Databricks Jobs for pipeline orchestration

Task dependencies and scheduling

Unity Catalog security model

Table and column-level access control

For the most up-to-date exam information, visit the official exam guide.

View Official Exam Guide

Databricks-DE-Associate

Databricks Data Engineer Associate Exam Guide

A 5-week study plan aligned to official Databricks-DE-Associate exam domains.

Exam Information

90 minutes

Duration

60 questions (approx.)

Questions

70%

Passing Score

See official exam pricing

Exam Cost

Recommended Study Plan

Week 1

Databricks Lakehouse Platform

24% of exam

6-8 hours

Focus: Unity Catalog is the governance layer — permissions, lineage, audit across workspaces
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#lakehouse-platform

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 2

ELT with Spark SQL & Python

29% of exam

10-12 hours

Focus: Prefer DataFrame API for complex pipelines; Spark SQL for ad-hoc analytics
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#elt-spark-sql-python

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 3

Incremental Data Processing

22% of exam

6-8 hours

Focus: CDC with MERGE INTO — match on key, update/insert/delete based on change type
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#incremental-data-processing

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 4

Production Pipelines

16% of exam

6-8 hours

Focus: Multi-task jobs replace legacy single-notebook job pattern
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#production-pipelines

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 5

Data Governance

9% of exam

6-8 hours

Focus: Row filters and column masks are Unity Catalog features — not manual views
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

Recommended Resources:

Databricks official objectives

/certifications/databricks/data-engineer-associate/notes#data-governance

/certifications/databricks/data-engineer-associate/practice

/certifications/databricks/data-engineer-associate/study-guide

Week 6

Final Review & Practice Exams

All domains

8-10 hours

Complete all three full-length practice exams
Review incorrect answers and weak domains
Revisit flashcards for key terms
Timed review of highest-weight domains

Recommended Resources:

Practice exams

Flashcards

Study notes PDF

Exam Tips & Strategies

Domain Insight 1

Unity Catalog is the governance layer — permissions, lineage, audit across workspaces

Domain Insight 2

Delta Lake provides ACID — plain Parquet on S3/ADLS does not

Follow Domain Weights

Spend more study time on higher-weighted domains — they drive the majority of exam questions.

Practice Under Time Pressure

Use timed practice exams to build pacing before test day.

Key Topics to Master

Data lakehouse concepts and architecture

Databricks workspace and notebooks

Extracting data from external sources

Loading data into Delta Lake tables

Delta Live Tables pipelines

Structured Streaming fundamentals

Databricks Jobs for pipeline orchestration

Task dependencies and scheduling

Unity Catalog security model

Table and column-level access control

For the most up-to-date exam information, visit the official exam guide.

View Official Exam Guide