The Databricks Certified Data Analyst Associate exam guide organizes the exam into nine sections and 39 objectives. Databricks publishes no percentage weights, but the objective counts show the shape: Executing Queries with Databricks SQL has nine, Dashboards and Visualizations seven, Analyzing Queries six, and the other six sections share the remaining seventeen.
Last updated September 2026.
| Data Analyst Associate | |
|---|---|
| Scored questions | 45 multiple-choice, some select-two; unscored items may be added without being identified |
| Time limit | 90 minutes |
| Passing score | Not published |
| Cost | US$200 |
| Prerequisite | None; six months of hands-on data analyst experience recommended |
| Delivery | Online proctored or test center |
| Validity | Two years, recertify by taking the current full exam |
All figures from the official Databricks Data Analyst Associate exam guide (30 October 2025 edition) and the certification page.
Because the guide gives no weights, the objective count per section is the only official signal of emphasis. Treat the shares below as a study-time guide, not as a promise about how many questions each section gets.
The core components and what each is for (Unity Catalog, Delta Lake, Databricks SQL, Lakeflow Jobs and pipelines, Mosaic AI, the Data Intelligence Engine); catalogs, schemas, managed and external tables, views, access controls, certified tables and lineage as Catalog Explorer shows them; and the role of Databricks Marketplace. The guide still names Delta Live Tables here; the product is now Lakeflow Spark Declarative Pipelines.
Discovering, querying and managing certified datasets in Unity Catalog; tagging an asset and reading its lineage in Catalog Explorer; and cleaning data in SQL, including removing invalid rows and handling missing values. Small, concrete, and worth an afternoon.
The approaches for bringing data in (ingestion from cloud storage, Delta Sharing with external systems, API-driven intake, Auto Loader, Marketplace) and uploading a file through the workspace UI. Two objectives, but the first one packs five paths and asks you to pick between them; see COPY INTO vs Auto Loader vs upload.
The largest section. The Databricks Assistant (now Genie Code) for writing and debugging queries; the role of a SQL warehouse; joining a Delta table with a federated source; materialized views, streaming tables and dynamic views and when each applies; aggregates including approximate count distinct; joins on single and multiple keys and the set operations union and union all; sorting and filtering; creating managed and external tables from CSV, Parquet and Delta sources; and Delta time travel. Nine objectives is almost a quarter of the guide, and every one is hands-on SQL.
Photon's features, benefits and supported workloads; finding poorly performing queries with Query Insights and the query profile; auditing and comparing results with Delta history; query history and caching to cut latency; Liquid Clustering to speed filtered queries on large tables; and fixing a query that returns the wrong result.
Building AI/BI dashboards with multiple pages, datasets and widgets; visualizations in notebooks and the SQL editor; defining and testing parameters; sharing with workspace users and groups, with external users through links, and by embedding in external apps; scheduling refreshes; configuring an alert with a threshold and destination; and choosing the visualization that communicates the insight.
The purpose, features and components of a Genie space; creating one with sample questions, instructions, a warehouse, curated Unity Catalog datasets and trusted assets; assigning permissions and distributing through embedded links and external apps; and optimizing with question tracking, feedback, benchmarks and refreshed metadata. The docs renamed Genie spaces to Genie Agents in July 2026; the questions use the guide's name. See Genie spaces for the exam.
Applying star, snowflake and data vault schemas to analytical workloads, and how they align with the medallion architecture. Two objectives, one trade-off: star vs snowflake vs data vault.
Unity Catalog roles and sharing settings; the three-level namespace of catalog, schema and tables or volumes; and storage and management best practices including table ownership and PII protection (column masks, row filters, dynamic views, tags).
| Section | Objectives | Share of 39 |
|---|---|---|
| 4. Executing Queries with Databricks SQL | 9 | ~23% |
| 6. Dashboards and Visualizations | 7 | ~18% |
| 5. Analyzing Queries | 6 | ~15% |
| 7. Genie Spaces | 4 | ~10% |
| 1, 2 and 9 | 3 each | ~8% each |
| 3 and 8 | 2 each | ~5% each |
Sections 4, 5 and 6 hold 22 of the 39 objectives. If your SQL is strong, that block is mostly Databricks-specific objects and tooling and moves quickly; if it is not, it is where the hours go. The five small sections are the cheapest marks: each is concrete, each maps to a few pages of documentation, and none should be left blank on a paper with no published cut score, since one overall total is all that counts.
The exam guide also carries six sample questions. Read them for the shape: every one is a scenario with a single best action, and the wrong options are real Databricks features applied to the wrong situation.
Nine sections covering 39 objectives: the Data Intelligence Platform, managing data, importing data, executing queries with Databricks SQL, analyzing queries, dashboards and visualizations, Genie spaces, data modeling, and securing data.
No. The exam guide lists sections and objectives but no percentages. Objective counts are the only official signal of emphasis, and Executing Queries with Databricks SQL has the most at nine of 39.
Section 4, Executing Queries with Databricks SQL and SQL Warehouses, with nine of the 39 objectives. Together with Analyzing Queries and Dashboards and Visualizations it covers 22 objectives, more than half the guide.
No. All nine sections are built around Databricks SQL, AI/BI dashboards, Genie spaces and Unity Catalog. SQL is the only language the objectives name.
The full guide lists every objective and six sample questions. It is the primary prep document and it is free.
Open the Databricks exam guide →