Databricks Certified Data Analyst Associate Lessons
39 lessons, one per exam-guide subdomain, in the order the guide teaches them. Every claim is cited to the official documentation.
Domain 1: Understanding of Databricks Data Intelligence Platform
3 lessons · 8% of the exam
1.1Databricks Platform Foundations: Lakehouse, Data Intelligence Engine, Delta Lake and Unity Catalog
Subdomain 1.1: Describe the core components of the Databricks Intelligence Platform, including Mosaic AI, DeltaLive tables, Lakeflow Jobs, Data Intelligence Engine, Delta Lake, Unity Catalog, and Databricks SQL.
2 pages · 23 min read
1.2Catalog Explorer Objects: Catalogs, Schemas, Managed and External Tables, Views
Subdomain 1.2: Understand catalogs, schemas, managed and external tables, access controls, views, certified tables, and lineage within the Catalog Explorer interface.
2 pages · 18 min read
1.3Databricks Marketplace: Role, Listing Types and OpenSharing
Subdomain 1.3: Describe the role and features of Databricks Marketplace.
2 pages · 20 min read
Domain 2: Managing Data
3 lessons · 8% of the exam
2.1Certify and Deprecate Data with Unity Catalog Tags
Subdomain 2.1: Use Unity Catalog to discover, query, and manage certified datasets.
2 pages · 20 min read
2.2Tag Data Assets in Catalog Explorer
Subdomain 2.2: Use the Catalog Explorer to tag a data asset and view its lineage.
2 pages · 20 min read
2.3Handling NULL and Missing Values in Databricks SQL
Subdomain 2.3: Perform data cleaning on Unity Catalog Tables in SQL, including removing invalid data or handling missing values.
2 pages · 19 min read
Domain 3: Importing Data
2 lessons · 5% of the exam
3.1Ingesting Files from S3 with Auto Loader, COPY INTO and File Upload
Subdomain 3.1: Explain the approaches for bringing data into Databricks, covering ingestion from S3, data sharing with external systems via Delta Sharing, API-driven data intake, the Auto Loader feature, and Marketplace.
2 pages · 18 min read
3.2Create a Delta Table by Uploading a File in the Databricks UI
Subdomain 3.2: Use the Databricks Workspace UI to upload a data file to the platform.
2 pages · 19 min read
Domain 4: Executing queries using Databricks SQL and Databricks SQL Warehouses
9 lessons · 23% of the exam
4.1Databricks Assistant (Genie Code) for SQL Query Writing and Debugging
Subdomain 4.1: Utilize Databricks Assistant within a Notebook or SQL Editor to facilitate query writing and debugging.
17 min read
4.2SQL Warehouses: The Compute Behind Every Databricks SQL Query
Subdomain 4.2: Explain the role a SQL Warehouse plays in query execution.
2 pages · 18 min read
4.3Lakehouse Federation Setup: Connections and Foreign Catalogs
Subdomain 4.3: Querying cross-system analytics by joining data from a Delta table and a federated data source.
2 pages · 18 min read
4.4Create and Refresh a Materialized View in Databricks SQL
Subdomain 4.4: Create a materialized view, including knowing when to use Streaming Tables and Materialized Views, and differentiate between dynamic and materialized views.
2 pages · 17 min read
4.5Counting Rows and Distinct Values: count and approx_count_distinct
Subdomain 4.5: Perform aggregate operations such as count, approximate count distinct, mean, and summary statistics.
2 pages · 19 min read
4.6SQL Joins and UNION vs UNION ALL in Databricks SQL
Subdomain 4.6: Write queries to combine tables using various join operations (inner, left, right, and so on) with single or multiple keys, as well as set operations like union and union all, including the differences between the joins (inner, left, right, and so on).
16 min read
4.7Sorting Databricks SQL Results: ORDER BY, SORT BY and LIMIT
Subdomain 4.7: Perform sorting and filtering operations on a table.
2 pages · 19 min read
4.8Managed vs External Tables in Unity Catalog
Subdomain 4.8: Create managed tables and external tables, including creating tables by joining data from multiple sources (e.g., CSV, Parquet, Delta tables) to create unified datasets, including Unity Catalog.
2 pages · 17 min read
4.9Delta Lake Time Travel: Querying Historical Table Versions
Subdomain 4.9: Use Delta Lake's time travel to access and query historical data versions.
2 pages · 17 min read
Domain 5: Analyzing Queries
6 lessons · 15% of the exam
5.1Photon Engine: Features, Benefits and Supported Workloads
Subdomain 5.1: Understand the Features, Benefits, and Supported Workloads of Photon.
13 min read
5.2Finding Slow Queries with Query History and system.query.history
Subdomain 5.2: Identify poorly performing queries in the Databricks Intelligence platform, such as Query Insights, Query Profiler log, etc.
2 pages · 19 min read
5.3Audit Delta Lake Table History with DESCRIBE HISTORY
Subdomain 5.3: Utilize Delta Lake to audit and view history, validate results, and compare historical results or trends.
2 pages · 18 min read
5.4Databricks SQL Query History: Find, Inspect and Debug Past Runs
Subdomain 5.4: Utilize query history and caching to reduce development time and query latency
2 pages · 19 min read
5.5Liquid Clustering: When It Speeds Up Filtered Queries
Subdomain 5.5: Apply Liquid Clustering to improve query speed when filtering large tables on specific columns.
2 pages · 19 min read
5.6Fixing SQL Queries That Return the Wrong Rows: NULLs and Joins
Subdomain 5.6: Fix a query to achieve the desired results.
2 pages · 21 min read
Domain 6: Working with Dashboards and Visualizations in Databricks
7 lessons · 18% of the exam
6.1AI/BI Dashboard Pages and Datasets
Subdomain 6.1: Build dashboards using AI/BI Dashboards, including multi-tabs/page layouts, multiple data sources/datasets, and widgets (visualizations, text, images).
2 pages · 20 min read
6.2Create and Manage Visualizations in Notebooks and the SQL Editor
Subdomain 6.2: Create visualizations in notebooks and the SQL editor.
2 pages · 19 min read
6.3Named Parameter Markers in Databricks SQL Queries
Subdomain 6.3: Work with parameters in SQL queries and dashboards, including defining, configuring, and testing parameters.
2 pages · 20 min read
6.4Publish and Share AI/BI Dashboards with Users, Groups, and Links
Subdomain 6.4: Configure permissions through the UI to share dashboards with workspace users/groups, external users through shareable links, and embed dashboards in external apps.
2 pages · 17 min read
6.5Schedule an AI/BI Dashboard Refresh: Create, Time and Manage Schedules
Subdomain 6.5: Schedule an automatic dashboard refresh.
2 pages · 18 min read
6.6Databricks SQL Alerts: Thresholds and Notification Destinations
Subdomain 6.6: Configure an alert with a desired threshold and destination.
16 min read
6.7Choosing Chart Types for Trends, Proportions, KPIs and Relationships
Subdomain 6.7: Identify the effective visualization type to communicate insights clearly.
2 pages · 18 min read
Domain 7: Developing, Sharing, and Maintaining AI/BI Genie spaces
4 lessons · 10% of the exam
7.1AI/BI Genie Spaces: Purpose and How Genie Answers Questions
Subdomain 7.1: Describe the purpose, key features, and components of AI/BI Genie spaces.
2 pages · 18 min read
7.2Create a Genie Space: Datasets, SQL Warehouse, and Sample Questions
Subdomain 7.2: Create 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.
2 pages · 18 min read
7.3Genie Space Permissions and Share Links
Subdomain 7.3: Assign permissions via the UI and distribute Genie spaces using embedded links and external app integrations.
2 pages · 17 min read
7.4Genie space monitoring: track questions, feedback, and fixes
Subdomain 7.4: Optimize AI/BI 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.
2 pages · 18 min read
Domain 8: Data Modeling with Databricks SQL
2 lessons · 5% of the exam
8.1Star and Snowflake Schemas for Analytical Workloads on Databricks
Subdomain 8.1: Apply industry-standard data modeling techniques, such as star, snowflake, and data vault schemas, to analytical workloads.
2 pages · 18 min read
8.2Medallion Architecture Layers and the Data Models in Each
Subdomain 8.2: Understand how industry-standard models align with the Medallion Architecture.
2 pages · 17 min read
Domain 9: Securing Data
3 lessons · 8% of the exam
9.1Unity Catalog Privileges: Namespace, Usage Rules and Inheritance
Subdomain 9.1: Use Unity Catalog roles and sharing settings to ensure workspace objects are secure.
2 pages · 22 min read
9.2Unity Catalog three-level namespace: catalogs, schemas, tables and volumes
Subdomain 9.2: Understand how the 3-level namespace(Catalog / Schema / Tables or Volumes) works in the Unity Catalog.
2 pages · 20 min read
9.3Unity Catalog Table Ownership and Secure Storage Best Practices
Subdomain 9.3: Apply best practices for storage and management to ensure data security, including table ownership and PII protection.
2 pages · 19 min read