Databricks Data Analyst study plan

Diagram the Databricks account-to-table hierarchy (account, workspace, metastore, catalog, schema, table, volume) from memory and label where Unity Catalog permissions apply

Compare serverless, pro, and classic SQL warehouse behavior and select an appropriate size and auto-stop policy for three stated workload scenarios

Write and execute ten SELECT queries against a sample catalog covering filtering, sorting, aliasing, CASE expressions, and NULL handling

Navigate Catalog Explorer, the SQL editor, query history, and the compute panel well enough to locate any saved query, its owner, and its run history

Compose multi-table queries using INNER, LEFT, and FULL OUTER joins and justify each join choice in a comment

Aggregate data with GROUP BY, HAVING, COUNT DISTINCT, and conditional aggregation to answer funnel and cohort-style questions

Solve ranking and running-total problems with window functions (ROW_NUMBER, RANK, SUM OVER, LAG/LEAD)

Use CTEs and subqueries to break a multi-step transformation into readable, testable stages

Parameterize a query with the query parameter widget and re-run it against two different values without editing SQL

Open the query profile for a slow query and identify the operator consuming the most time

Distinguish shuffle, spill, and scan bottlenecks and state one remediation for each

Read EXPLAIN and EXPLAIN EXTENDED output to confirm predicate pushdown and join strategy

Rewrite three slow queries using filtering before joins, fewer wide shuffles, or pre-aggregation

Apply Photon and result caching deliberately and measure the effect with and without each

Interpret every metric shown in a query profile (rows read, bytes read, spill, shuffle, task counts, queue time) and explain what each implies

Diagnose a slow dashboard tile by tracing it back to its source query and warehouse queueing behavior

Evaluate partition and liquid clustering choices for a given table and predict their effect on scan volume

Complete a timed 30-question practice set covering domains 1, 4, and 5 and review every miss against documentation

Build a dashboard containing at least four chart types (bar, line, pie or counter, table) from saved queries

Add a dashboard-level filter and a parameter so a viewer can switch the analysis dimension without editing SQL

Configure a refresh schedule and set appropriate permissions for a viewer group

Choose an appropriate visualization for a given metric shape and document when a table beats a chart

Export or embed dashboard results and verify the numbers match the underlying query output

Create an AI/BI Genie space pointed at a curated set of tables and verify it answers basic questions correctly

Write space instructions, synonyms, and example SQL that steer Genie toward correct joins and metric definitions

Maintain a benchmark list of 12 natural-language questions with verified expected answers and score Genie's accuracy against it

Iterate on space configuration (table selection, sample values, instructions) and measure whether accuracy improves between runs

Set sharing and permission settings so the right audience can query the space without over-exposing tables

Import data using the UI upload, CREATE TABLE from files, and COPY INTO, and state when each is appropriate

Create a managed table and an external table and describe how each behaves on DROP

Run OPTIMIZE and VACUUM on a table and explain the tradeoffs of each, including how VACUUM affects time travel

Query historical table versions with time travel and inspect lineage to identify upstream and downstream dependencies

Fix three deliberately failing Genie questions by improving table comments, column comments, or instructions

Design a star schema with one fact table and two dimension tables, assign surrogate keys, and document grain in one sentence

Apply primary key, foreign key, and NOT NULL constraints and explain how informational constraints differ from enforced ones

Grant catalog, schema, and table privileges to a group and verify access with a least-privilege test account

Implement a row filter and a column mask on a table and confirm both behave as intended for two different users

Take a full-length timed practice exam and produce a prioritized remediation list from the results