Exam Prep – Databricks Certified Data Analyst Associate
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Learning Track
Exam Prep
Delivery methods
On-Site, Virtual
Duration
1 day
This course prepares learners for the Databricks Certified Data Analyst Associate exam using the updated September 2025 exam guide. The approach is question-driven: each module is centered on realistic exam-style questions aligned to the official domains. Instructors walk through every option — why it is correct or incorrect — and blend in concise teaching to reinforce Databricks SQL, ingestion, governance, visualization, and analytics concepts.
Learning Objectives
By the end of this course, learners will be able to:
- Confidently answer questions across all exam domains in the new 2025 guide.
- Understand the reasoning behind correct and incorrect answers.
- Apply Databricks SQL and data analysis concepts to ingestion, dashboards, governance, and analytics workflows.
- Strengthen readiness for both the exam and real-world data analysis tasks.
Audience
- Candidates preparing for the Databricks Certified Data Analyst Associate exam after September 30, 2025
- Data analysts with ~6 months of Databricks experience
- Learners who prefer practice-driven exam preparation over traditional lecture-heavy study
Prerequisites
- Intermediate SQL knowledge
- Hands-on experience with Databricks SQL, Unity Catalog, and dashboarding
- Familiarity with data ingestion and management workflows
Course outline
- Certification format, domains, scoring, timing
- Strategies for analyzing multiple-choice questions
- Question types and common distractors
- Pacing strategies and flagging questions for review
- Unity Catalog for discovering, querying, cleaning, and certifying datasets
- Ingestion methods: UI loading, API ingestion, Auto Loader, Delta Sharing, Marketplace
- Permissions, lineage, and catalog governance
- Creating and managing views
- Aggregate functions, filtering logic, and joins
- Query performance optimization and caching strategies
- Filtering, aggregation, joins, and subqueries
- MERGE, INSERT, and COPY INTO operations
- Working with nested data, rollups, cubes, and window functions
- Using UDFs for extended analysis
- Building tables, counters, pivots, and styled charts
- Adding parameters, filters, and interactivity
- Scheduling dashboard refreshes and creating alerts
- Sharing and collaboration practices
- Applying statistical concepts: descriptive measures, distributions, continuous vs. discrete
- Data blending and last-mile ETL within analytics workflows
- Using dashboards and SQL queries to solve end-to-end business scenarios
