Databricks Data Analyst study guide
Databricks Data Analyst · Work through your exam, one topic at a time.
The Databricks Certified Data Analyst Associate is an entry-level, proctored certification that validates a candidate's ability to use the Databricks Data + AI Platform and Databricks SQL to complete introductory data analysis work. According to the official exam page, it assesses proficiency across the platform itself, managing data with Unity Catalog, importing data through methods such as the UI, S3 ingestion, Delta Sharing, API-driven intake, Auto Loader, and Marketplace, and executing and optimizing queries - including creating views, performing aggregations, joining, filtering, and sorting tables, and analyzing queries with auditing, history, logs, and Liquid clustering. The Databricks Data Analyst study guide has 9 sections and about 3,289 words.
01Understanding the Databricks Data + AI Platform
Databricks combines a data lakehouse - cheap cloud object storage (S3, ADLS, GCS) managed in Delta Lake format - with a managed control plane that runs workspaces, notebooks, jobs, and metadata. The critical split: the control plane lives in Databricks' account; the data plane (your data and often the compute VMs) lives in your cloud account or, for serverless, in Databricks-managed infrastructure inside your region.
366 words, about 2 min02Managing Data
The single most tested distinction. A managed table's data files are owned by Unity Catalog and deleted when you DROP TABLE .
371 words, about 2 min03Importing Data
Know which tool fits which scenario - questions are almost always phrased as "which approach is best ." UI upload / Create Table from file - quick, small files, good for demos and one-offs. COPY INTO - SQL command that loads files from cloud storage into a Delta target.
356 words, about 2 min04Executing Queries with Databricks SQL and SQL Warehouses
A SQL warehouse is a compute resource dedicated to Databricks SQL. Types: Serverless - Databricks-managed infrastructure, fastest start, no cluster configuration, scales instantly.
359 words, about 2 min05Analyzing Queries
Query History lists every statement with duration, status, warehouse, user, and rows/bytes read. Clicking a query opens Query Profile , a visual plan showing operators, rows, and time per stage.
365 words, about 2 min06Creating Dashboards and Visualizations in Databricks
A dashboard is a collection of datasets (SQL queries), visualizations built from those datasets, and pages that arrange them. Adding a dataset means writing SQL against tables in Unity Catalog; the dashboard executes it on a chosen SQL warehouse.
388 words, about 2 min07Developing, Sharing, and Maintaining AI/BI Genie Spaces
An AI/BI Genie space lets business users ask questions in natural language and receive SQL-backed answers, tables, and charts. Genie is not a general chatbot: it reasons over a curated semantic context you provide, so answer quality is a function of curation quality.
357 words, about 2 min08Data Modeling with Databricks SQL
The expected pattern for analytics is a star schema : central fact tables at the grain of a business event (one row per order line, per session), surrounded by conformed dimension tables (customer, product, date). Keep facts narrow and numeric; keep dimensions descriptive.
371 words, about 2 min09Securing Data
Unity Catalog secures objects in a nested hierarchy: metastore → catalog → schema → table/view/volume/function . Privileges granted at a higher level are inherited by everything beneath it.
356 words, about 2 min