Databricks Certified Data Analyst Associate¶

Exam Overview¶

The Databricks Certified Data Analyst Associate exam tests whether you can do basic analytics tasks on the Databricks Data Intelligence Platform: find and manage governed data with Unity Catalog, import it, query it with Databricks SQL, tune and troubleshoot queries, build AI/BI dashboards and alerts, create and maintain Genie agents, model data for analytics and keep it secure. Everything is SQL (ANSI standard) and no Python is required.

Exam Details (from the 📖 exam page and 📖 exam guide, read 2026-11-07): - Exam Name: Databricks Certified Data Analyst Associate (no separate code) - Duration: 90 minutes - Number of Questions: 45 scored multiple-choice questions, plus up to 10 unscored - Passing Score: Not published - Cost: $200 USD plus taxes - Delivery: Online proctored or test center; no test aids - Languages: English - Validity: 2 years; retakes after 14 days at full price - Prerequisites: None; 6+ months of hands-on analysis recommended

Exam Sections¶

Question counts apply the weights to 45 scored items, rounded; Databricks does not publish per-section counts.

What each section covers¶

1. Platform - Delta Lake, Unity Catalog, Databricks SQL, Lakeflow, Mosaic AI, Lakebase; catalogs, schemas, managed and external tables, views, metric views, lineage; Marketplace.
2. Managing Data - discover certified datasets, governed tags, lineage, cleaning with SQL.
3. Importing Data - S3 and Auto Loader, managed connectors, Delta Sharing, API intake, Marketplace; UI upload.
4. Executing Queries - SQL warehouses, Genie Code, federation, materialized views versus streaming tables, aggregates, joins, unions, tables, time travel.
5. Analyzing Queries - Photon, query history and profile, Delta audit, caching, Predictive Optimization, Liquid Clustering, fixing queries.
6. Dashboards - AI/BI dashboards, visualizations, parameters, sharing and embedding, refresh schedules, alerts, chart choice.
7. Genie Agents - purpose and components, creation, permissions and distribution, optimization with benchmarks and feedback.
8. Data Modeling - star, snowflake, data vault; alignment with Medallion.
9. Securing Data - privileges, ownership, three-level namespace, PII.

Names to know¶

Study Approach¶

Phase 1: Data and queries (Weeks 1-3)¶

1. Sections 1-3 briefly, then Section 4 slowly: write every join and aggregate yourself in Free Edition.
2. Section 5: use Query History and the query profile on your own queries.

Phase 2: Dashboards and Genie (Weeks 3-4)¶

1. Section 6: build a two-page dashboard with a date parameter and create an alert.
2. Section 7: create a Genie agent on a small schema, add instructions and a benchmark.

Phase 3: Model, secure, review (Week 5)¶

1. Sections 8 and 9, then practice questions and the "How the exam tests this section" endings.

Study Resources¶

• 📖 Exam page - format, fee, registration
• 📖 Exam guide PDF - objectives, sample questions and answer key
• 📖 Databricks Free Edition - free workspace
• 📖 Databricks documentation - authoritative reference
• Courses named in the guide (plain text, names change): Data Analysis with Databricks (instructor-led); AI/BI for Data Analysts and SQL Analytics on Databricks (self-paced, Databricks Academy)

Tips for Success¶

1. SQL fluency is the core. Sections 4-6 are about half the exam.
2. Know which object to create (view, materialized view, streaming table).
3. Use current names; older materials say Assistant and Genie spaces.
4. Understand why a query is wrong, not just how to write it.

File Index¶