Most people need 3 to 4 weeks of part-time study, roughly 25 to 35 hours, to pass the Databricks Certified Data Analyst Associate exam. If you already write SQL in Databricks and publish AI/BI dashboards, 1 to 2 weeks of review is realistic. Coming from spreadsheets or a different BI tool with little SQL, budget 6 to 8 weeks.
Last updated September 2026.
These assume 7 to 8 hours a week. The exam has no prerequisite; Databricks recommends about six months of hands-on work as a data analyst as background, not a gate. The number that predicts readiness is not weeks on the calendar, it is whether you can write the query, read its profile, and publish the result without looking anything up.
Exam facts (no prerequisite, 45 scored questions, 90 minutes) come from the official Databricks exam guide. The timelines are our own estimates.
The exam serves 45 scored questions in 90 minutes against the 39 objectives in the official guide. The guide groups them into nine sections and publishes no weights, so the objective counts are the best available signal for where the hours go.
| Exam section | Objectives | Share of the 39 |
|---|---|---|
| 4. Executing Queries with Databricks SQL | 9 | About 23% |
| 6. Dashboards and Visualizations | 7 | About 18% |
| 5. Analyzing Queries | 6 | About 15% |
| 7. Genie Spaces | 4 | About 10% |
| 1. The Data Intelligence Platform | 3 | About 8% |
| 2. Managing Data | 3 | About 8% |
| 9. Securing Data | 3 | About 8% |
| 3. Importing Data | 2 | About 5% |
| 8. Data Modeling | 2 | About 5% |
Sections and objective counts are from the official Databricks Data Analyst Associate exam guide (30 October 2025 edition). The guide publishes no percentage weights, so the shares are derived from objective counts, not official figures.
Sections 4, 5 and 6 are 22 of the 39 objectives: write the query, understand its performance, publish the result. If your SQL is already strong, most of that block is learning Databricks-specific objects and tooling, which goes quickly. If it is not, the SQL itself is the long part of the plan.
Build one dashboard and one Genie space before the exam. Publish a dashboard with a parameter and a schedule, then point a Genie space at its datasets. Sections 6 and 7 stop being vocabulary the moment you have shipped each once.
Databricks publishes no cut score, so the honest test is consistency: two full-length timed mocks, both above 70 percent, with no section blank. Certify's practice hub for the course tracks mastery per section from every session you run and recommends the weakest one next, which is a quicker signal than re-reading chapters you already know.
Most people need 3 to 4 weeks of part-time study, roughly 25 to 35 hours. Analysts already working in Databricks SQL can be ready in 1 to 2 weeks, and those with light SQL from a spreadsheet or BI-tool background should budget 6 to 8 weeks.
Around 25 to 35 hours at 7 to 8 hours a week for the typical candidate. More than half of that belongs in Databricks SQL, analyzing queries and dashboards, which together are 22 of the 39 objectives.
It is an associate-level exam with no prerequisite, but the questions are scenario-based and some ask you to select two answers. Strong SQL and hands-on time with AI/BI dashboards and Genie spaces are what separate a pass from a near miss.
No. The exam is built around Databricks SQL, dashboards and Genie spaces, so SQL is the language you need. Python appears nowhere in the nine sections of the exam guide.
No, there is no prerequisite. Databricks recommends about six months of hands-on work as a data analyst as background, but it is a recommendation, and focused study plus building one dashboard and one Genie space can stand in for much of it.
Chapter 1 takes two minutes. Work through the nine units at your own pace and let the section exams and mocks tell you when you are ready.
Start Chapter 1 →