Databricks Certified Data Analyst Associate Practice Test

This certification is designed for data analysts, business intelligence professionals, SQL practitioners, and business users who work with or plan to work with the Databricks Data Intelligence Platform. It is well-suited for individuals in roles such as Data Analyst, BI Analyst, Analytics Engineer, or SQL Developer who need to demonstrate hands-on proficiency with Databricks SQL for querying, visualization, and insight generation.

Candidates are expected to have approximately 6 months of hands-on experience performing data analysis tasks within the Databricks environment. The associate-level designation makes it an appropriate starting point for professionals transitioning into the Lakehouse ecosystem or those looking to formalize their existing Databricks SQL skills with a vendor-recognized credential.

There are no mandatory formal prerequisites to register for this exam. However, Databricks recommends that candidates have at least 6 months of practical, hands-on experience working with Databricks SQL and the Data Intelligence Platform before attempting the exam. Familiarity with ANSI SQL standards is essential, as all SQL in the exam conforms to that specification.

Databricks also recommends completing the Lakehouse Fundamentals Accreditation as a foundational step before pursuing this certification. Prior experience with Unity Catalog for data governance, Delta Lake for data management, and the Databricks SQL editor will be highly beneficial. Candidates without Databricks-specific experience but with strong SQL backgrounds and data warehouse or analytics tool experience may still be competitive after targeted hands-on preparation.

The exam consists of 45 scored questions delivered in a 90-minute time window. Questions are multiple-choice and multi-select format. The exam may also include a small number of unscored survey or pilot items used for statistical calibration of future exams; these items are not identified and do not affect the final score, with additional time factored in to account for them.

The passing score is 70%. The exam costs USD $200 (plus applicable local taxes) and is delivered online through Databricks' exam delivery platform, which requires account creation or login prior to registration. All SQL tested on the exam adheres to ANSI SQL standards. Recertification is required every two years by retaking the current version of the exam.

• 1.Databricks SQL (22%): Understanding the features, capabilities, and architecture of the Databricks SQL service, including workspace configuration, SQL warehouses, query editor functionality, alerts, and integration with the broader Data Intelligence Platform.
• 2.Data Management (20%): Managing data using Unity Catalog, including discovering, querying, cleaning, and governing certified datasets. Covers data ingestion methods such as UI-based uploads, S3 ingestion, Delta Sharing, API-driven intake, Auto Loader, and the Databricks Marketplace. Also includes Delta Lake table management, metadata handling, and data storage best practices.
• 3.SQL (29%): Writing and executing ANSI SQL-compliant queries for data exploration and analysis within the Lakehouse environment. Topics include JOIN operations, subqueries, aggregate functions, filtering, sorting, combining data from multiple sources, creating views, and auditing query performance using history logs and Liquid Clustering features.
• 4.Data Visualization and Dashboards (18%): Creating production-grade data visualizations and AI/BI dashboards using Databricks SQL. Includes selecting appropriate chart types, configuring dashboard parameters, setting up alerts, sharing dashboards with stakeholders, and developing AI/BI Genie spaces for natural-language-driven analytics.
• 5.Analytics Applications (11%): Applying data analysis techniques to solve common business problems using Databricks SQL. Covers building analytics workflows, performing data transformations, and leveraging platform features to deliver actionable insights.

• Download and study the official Databricks Certified Data Analyst Associate Exam Guide PDF from files.training.databricks.com — it lists all exam domains, topic breakdowns, and sample question styles. Use it as your primary study roadmap.
• Complete the official 'Data Analysis with Databricks' self-paced course on Databricks Academy (academy.databricks.com). It directly covers ingest, querying, dashboards, and alerting — the core exam content — and is explicitly designed to prepare candidates for this exam.
• Get hands-on with a live Databricks Community Edition account. Practice writing ANSI SQL queries in the SQL editor, create dashboards using AI/BI, configure alerts, and experiment with Unity Catalog to manage tables and permissions. Practical exposure is the most effective preparation.
• Focus significant study time on the SQL domain (29% weight), which is the largest section. Practice JOINs, subqueries, window functions, aggregations, and filtering on Databricks SQL. Pay attention to behaviors specific to Delta Lake tables such as DESCRIBE HISTORY and time travel queries.
• Study Unity Catalog governance concepts thoroughly for the Data Management domain (20%). Understand the three-level namespace (catalog.schema.table), data lineage, grants and privileges, ABAC, and the differences between managed and external tables in the Lakehouse.
• Review the AI/BI Genie spaces feature and the newer dashboard capabilities introduced in the 2025 exam update. This includes configuring parameters, sharing dashboards, embedding visualizations, and understanding when to use Genie spaces versus traditional dashboards.
• Take at least two full-length timed practice exams before the real test. Udemy offers several highly-rated practice exam sets specific to this certification. Review all incorrect answers against the official exam guide to close knowledge gaps before exam day.

Earning the Databricks Certified Data Analyst Associate credential signals verified proficiency on one of the fastest-growing data platforms in the enterprise market. Databricks is widely adopted by companies building Lakehouse architectures, and certified analysts are well-positioned for roles such as Data Analyst, BI Analyst, Analytics Engineer, and SQL Developer at organizations using Databricks. The certification is particularly valuable for professionals looking to differentiate themselves as Databricks skills become a standard hiring requirement across data teams.

Data analysts with Databricks certification report average salaries in the range of $115,000–$148,000 annually in the United States, meaningfully above the general data analyst average. The certification is an associate-level entry point into the Databricks certification ecosystem, which also includes Data Engineer Associate/Professional and Machine Learning tracks, giving certified analysts a clear pathway for continued credential advancement. As enterprises continue to consolidate their data and AI workloads on unified Lakehouse platforms, demand for analysts with validated Databricks SQL and governance skills is expected to remain strong.