Databricks DA Assoc study guide · 2026

The 9 Databricks DA Assoc domains, explained

9 domains and 39 official objectives. Executing queries using Databricks SQL and Databricks SQL Warehouses carries the most weight at 20%. Each guide explains what the domain covers, how its questions are framed and where candidates lose marks.

Start with Domain 4 See all domains
Questions
45 scored multiple-choice questions (plus unscored items)
Time
90 minutes
Passing score
Not published by Databricks
Outline
Databricks Certified Data Analyst Associate exam guide, August 2026 edition (updated 8 Oct 2026, live 19 Oct 2026; current)

Exam blueprint

Bar widths follow the official weights. Weight ranges are drawn at their midpoint.

  1. 1 11%
  2. 2 8%
  3. 3 5%
  4. 4 20%
  5. 5 15%
  6. 6 16%
  7. 7 12%
  8. 8 5%
  9. 9 8%
  1. 1 Understanding of Databricks Data Intelligence Platform (Lakehouse Platform)
  2. 2 Managing Data
  3. 3 Importing Data
  4. 4 Executing queries using Databricks SQL and Databricks SQL Warehouses
  5. 5 Analyzing Queries
  6. 6 Working with Dashboards and Visualizations in Databricks
  7. 7 Developing, Sharing, and Maintaining AI/BI Genie Agents (Genie Spaces)
  8. 8 Data Modeling with Databricks SQL
  9. 9 Securing Data

All 9 domains

39 official objectives 53–79 hrs suggested study

  1. Domain 01 11%

    Understanding of Databricks Data Intelligence Platform (Lakehouse Platform)

    Section 1 checks that you know what each part of the Databricks Data Intelligence Platform does, how Unity Catalog objects appear in Catalog Explorer, and what Databricks Marketplace offers an analyst.

    Inside this domain

    • Describe the core components of the Databricks Data Intelligence Platform (Lakehouse Platform), including Mosaic AI, Lakeflow Declarative Pipelines (DeltaLive tables), Lakeflow Jobs, Data Intelligence Engine, Delta Lake, Lakebase, Unity Catalog, and Databricks SQL.
    • Understand catalogs, schemas, managed and external tables, access controls, views, certified tables, metric views, and lineage within the Catalog Explorer interface.
    • Describe the role and features of Databricks Marketplace.

    Watch for Pipelines versus Jobs

    Objectives
    3
    Questions est.
    ~5
    Study time est.
    5–8 hrs
  2. Domain 02 8%

    Managing Data

    Section 2 is about the day-to-day handling of governed data: finding and using certified datasets in Unity Catalog, tagging assets with governed tags, following lineage, and cleaning tables with SQL.

    Inside this domain

    • Use Unity Catalog to discover, query, and manage certified datasets.
    • Use the Catalog Explorer to tag a data asset with governed tags and view its lineage, including external lineage.
    • Perform data cleaning on Unity Catalog Tables in SQL, including removing invalid data or handling missing values.

    Watch for Filtering instead of filling

    Objectives
    3
    Questions est.
    ~4
    Study time est.
    4–6 hrs
  3. Domain 03 5%

    Importing Data

    Section 3 asks you to choose the right way to bring data into Databricks, from cloud storage, shares, APIs, Auto Loader, Lakeflow Connect connectors and Marketplace, and to upload a file through the workspace UI.

    Inside this domain

    • Explain the approaches for bringing data into Databricks, covering ingestion from S3, data sharing with external systems via Delta Sharing, API-driven data intake, Auto Loader, Lakeflow Connect managed connectors, and Marketplace.
    • Use the Databricks Workspace UI to upload a data file to the platform.

    Watch for Auto Loader for SaaS

    Objectives
    2
    Questions est.
    ~2
    Study time est.
    3–5 hrs
  4. Domain 04 20%

    Executing queries using Databricks SQL and Databricks SQL Warehouses

    The largest section at 20%. It covers writing and running SQL on SQL warehouses: Genie Code help, federated joins, materialized views, aggregates, joins and set operations, sorting and filtering, table creation and Delta time travel.

    Inside this domain

    • Utilize Genie Code (Databricks Assistant) within a Notebook or SQL Editor to facilitate query writing and debugging.
    • Explain the role a SQL Warehouse plays in query execution.
    • Querying cross-system analytics by joining data from a Delta table and a federated data source.
    • Create a materialized view, including knowing when to use Streaming Tables and Materialized Views, and differentiate between dynamic and materialized views.
    • and 5 more objectives

    Watch for Size versus scale-out

    Objectives
    9
    Questions est.
    ~9
    Study time est.
    12–16 hrs
  5. Domain 05 15%

    Analyzing Queries

    Section 5 covers why queries run slowly or return wrong results and what to do about it: Photon, query profiles and insights, Delta history, caching, Predictive Optimization, automatic liquid clustering and correcting SQL.

    Inside this domain

    • Understand the Features, Benefits, and Supported Workloads of Photon.
    • Identify poorly performing queries in the Databricks Intelligence platform, such as Query Insights, Query Profiler log, etc.
    • Utilize Delta Lake to audit and view history, validate results, and compare historical results or trends.
    • Utilize query history and caching to reduce development time and query latency.
    • and 2 more objectives

    Watch for Bigger warehouse for poor pruning

    Objectives
    6
    Questions est.
    ~7
    Study time est.
    8–12 hrs
  6. Domain 06 16%

    Working with Dashboards and Visualizations in Databricks

    Section 6 tests building and running AI/BI Dashboards: layouts, datasets and widgets, charts in notebooks and the SQL editor, parameters, sharing and embedding, refresh schedules, alerts and choosing the right chart.

    Inside this domain

    • Build dashboards using AI/BI Dashboards, including multi-tabs/page layouts, multiple data sources/datasets, and widgets (visualizations, text, images).
    • Create visualizations in notebooks and the SQL editor.
    • Work with parameters in SQL queries and dashboards, including defining, configuring, and testing parameters.
    • Configure permissions through the UI to share dashboards with workspace users/groups, external users through shareable links, and embed dashboards in external apps.
    • and 3 more objectives

    Watch for Filter for logic changes

    Objectives
    7
    Questions est.
    ~7
    Study time est.
    8–12 hrs
  7. Domain 07 12%

    Developing, Sharing, and Maintaining AI/BI Genie Agents (Genie Spaces)

    Section 7 covers AI/BI Genie Agents, still widely called Genie spaces: what they are, how to build them with curated data, instructions and trusted assets, how to share them, and how to keep their answers accurate.

    Inside this domain

    • Describe the purpose, key features, and components of AI/BI Genie Agents (Genie spaces).
    • Create Genie Agents (Genie spaces) by defining reasonable sample questions and domain-specific instructions, choosing SQL warehouses, curating Unity Catalog datasets (tables, views...), and vetting queries as Trusted Assets.
    • Assign permissions via the UI and distribute Genie Agents (Genie spaces) using embedded links, external app integrations, and channel apps.
    • Optimize AI/BI Genie Agents (Genie spaces) by tracking user questions, response accuracy, and feedback; updating instructions and trusted assets based on stakeholder input; validating accuracy with benchmarks; refreshing Unity Catalog metadata.

    Watch for More data for better answers

    Objectives
    4
    Questions est.
    ~5
    Study time est.
    6–9 hrs
  8. Domain 08 5%

    Data Modeling with Databricks SQL

    Section 8 checks that you can apply star, snowflake and data vault models to analytical workloads in Databricks SQL and explain where each fits within the bronze, silver and gold layers of the Medallion Architecture.

    Inside this domain

    • Apply industry-standard data modeling techniques, such as star, snowflake, and data vault schemas, to analytical workloads.
    • Understand how industry-standard models align with the Medallion Architecture.

    Watch for Normalised dimensions as star

    Objectives
    2
    Questions est.
    ~2
    Study time est.
    3–5 hrs
  9. Domain 09 8%

    Securing Data

    Section 9 covers protecting data with Unity Catalog: privileges and sharing settings on securable objects, how the catalog, schema and table or volume namespace works, and good practice for ownership and personal data.

    Inside this domain

    • Use Unity Catalog roles and sharing settings to ensure workspace objects are secure.
    • Understand how the 3-level namespace (Catalog / Schema / Tables or Volumes) works in the Unity Catalog.
    • Apply best practices for storage and management to ensure data security, including table ownership and PII protection.

    Watch for SELECT alone

    Objectives
    3
    Questions est.
    ~4
    Study time est.
    4–6 hrs

Study the heaviest domains first

Marks follow weight. This order puts the most marks behind you first, across about 53–79 hrs of study.

  1. 4 Executing queries using Databricks SQL and Databricks SQL Warehouses 20% · 12–16 hrs
  2. 6 Working with Dashboards and Visualizations in Databricks 16% · 8–12 hrs
  3. 5 Analyzing Queries 15% · 8–12 hrs
  4. 7 Developing, Sharing, and Maintaining AI/BI Genie Agents (Genie Spaces) 12% · 6–9 hrs
  5. 1 Understanding of Databricks Data Intelligence Platform (Lakehouse Platform) 11% · 5–8 hrs
  6. 2 Managing Data 8% · 4–6 hrs
  7. 9 Securing Data 8% · 4–6 hrs
  8. 3 Importing Data 5% · 3–5 hrs
  9. 8 Data Modeling with Databricks SQL 5% · 3–5 hrs

Try one

Practice questionDomain 4: Executing queries using Databricks SQL and Databricks SQL Warehouses

A dashboard runs an expensive join and aggregation over three large Delta tables every few minutes. The data changes hourly, and users accept results up to one hour old. What should the analyst create?

One trap from every domain

The answer that looks right, and the clue that gives it away.

  • Domain 1

    Pipelines versus Jobs

    Clue Words like schedule, trigger, retry or task order.

  • Domain 2

    Filtering instead of filling

    Clue Keep all rows, replace missing values.

  • Domain 3

    Auto Loader for SaaS

    Clue A named SaaS application or database source.

  • Domain 4

    Size versus scale-out

    Clue Many users, queries waiting in queue.

  • Domain 5

    Bigger warehouse for poor pruning

    Clue Few files pruned, large bytes scanned.

  • Domain 6

    Filter for logic changes

    Clue The value must change a calculation.

  • Domain 7

    More data for better answers

    Clue Genie picks the wrong table or column.

  • Domain 8

    Normalised dimensions as star

    Clue Product links to a separate category table.

Other Data & Analytics certifications

Study guides for exams that overlap with Databricks DA Assoc.

Practise what you read

Databricks DA Assoc domains: common questions

How many domains are in the Databricks DA Assoc exam?

Databricks DA Assoc has 9 domains with 39 official objectives between them: Understanding of Databricks Data Intelligence Platform (Lakehouse Platform), Managing Data, Importing Data, Executing queries using Databricks SQL and Databricks SQL Warehouses, Analyzing Queries, Working with Dashboards and Visualizations in Databricks, Developing, Sharing, and Maintaining AI/BI Genie Agents (Genie Spaces), Data Modeling with Databricks SQL and Securing Data.

Which Databricks DA Assoc domain carries the most weight?

Executing queries using Databricks SQL and Databricks SQL Warehouses is the heaviest at 20%, followed by Working with Dashboards and Visualizations in Databricks (16%). The lightest is Data Modeling with Databricks SQL (5%). Weights come from Databricks's official outline.

What is the Databricks DA Assoc exam format?

Questions: 45 scored multiple-choice questions (plus unscored items). Time allowed: 90 minutes. Passing score: Not published by Databricks.

How long should I study for Databricks DA Assoc?

Our planning estimate is 53–79 hrs across all domains, split by weight. It is an editorial estimate, not an official figure, so adjust it to your experience and to how you score on practice questions.

Where should I start?

Start with Executing queries using Databricks SQL and Databricks SQL Warehouses, because it carries the most marks, then work down by weight. Use the checklist on each domain page to confirm you can do what the domain asks before moving on.

Which outline is this guide based on?

This guide follows Databricks Certified Data Analyst Associate exam guide, August 2026 edition (updated 8 Oct 2026, live 19 Oct 2026; current), published by Databricks. It was last reviewed in October 2026.

Domain names, weights and objectives come from Databricks's official outline (Databricks Certified Data Analyst Associate exam guide, August 2026 edition (updated 8 Oct 2026, live 19 Oct 2026; current)). Question counts and study hours are editorial planning estimates, not official figures. Last reviewed October 2026.