Databricks Certified Data Analyst Associate - Study Guide

This comprehensive study guide maps relevant Databricks documentation to each section of the exam guide to help you prepare for the Databricks Certified Data Analyst Associate certification.

Section 1: Databricks SQL

Key Audience and SQL Benefits

• Relevant Documentation:
  • Databricks SQL concepts - Fundamental concepts for understanding Databricks SQL
  • What is data warehousing on Databricks? - Overview of SQL and lakehouse capabilities
  • Get started with data warehousing using Databricks SQL - Getting started guide for data analysts

Basic Databricks SQL Queries

• Relevant Documentation:
  • Write queries and explore data in the SQL editor - Complete guide to the SQL editor interface
  • Query data - Core concepts for querying data in Databricks
  • SQL language reference - Complete SQL syntax reference

Schema Browser and Query Editor Features

• Relevant Documentation:
  • Write queries and explore data in the SQL editor - Schema browser and editor features
  • Query data - Understanding the query interface

Dashboards and Visualization

• Relevant Documentation:
  • Dashboards - Complete dashboard creation and management guide
  • Table visualizations - Specific visualization types in dashboards

SQL Endpoints/Warehouses

• Relevant Documentation:
  • Connect to a SQL warehouse - Understanding SQL warehouses
  • Configure SQL warehouses - Warehouse configuration and management
  • SQL warehouse types - Serverless vs Pro vs Classic warehouses
  • SQL warehouse sizing, scaling, and queuing behavior - Performance characteristics
  • Enable serverless SQL warehouses - Serverless setup and limitations

Partner Connect and External Tool Integration

• Relevant Documentation:
  • What is Databricks Partner Connect? - Overview of Partner Connect functionality
  • Business intelligence tools - BI tool integration overview
  • Connect Tableau and Databricks - Tableau integration guide
  • Connect Power BI to Databricks - Power BI integration guide

Data Import and Small File Upload

• Relevant Documentation:
  • Upload files to Databricks - File upload options overview
  • Create or modify a table using file upload - Small file upload for lookup tables
  • Work with files on Databricks - File management options

COPY INTO and Object Storage Integration

• Relevant Documentation:
  • Get started using COPY INTO to load data - Basic COPY INTO usage
  • Load data using COPY INTO with Unity Catalog volumes or external locations - Unity Catalog integration
  • Common data loading patterns using COPY INTO - Advanced patterns and examples

Medallion Architecture

• Relevant Documentation:
  • What is the medallion lakehouse architecture? - Complete guide to bronze/silver/gold layers
  • What is data warehousing on Databricks? - How medallion architecture fits with data warehousing
  • Get started: Enhance and cleanse data - Practical example of silver/gold transformation

Streaming Data and Lakehouse Capabilities

• Relevant Documentation:
  • What is a data lakehouse? - Lakehouse architecture and streaming capabilities
  • Lakehouse reference architectures - Architectural patterns including streaming

Section 2: Data Management

Delta Lake Fundamentals

• Relevant Documentation:
  • What is Delta Lake in Databricks? - Core Delta Lake concepts
  • Tutorial: Delta Lake - Hands-on Delta Lake operations
  • Best practices: Delta Lake - Optimization and best practices

Delta Lake Table Management and History

• Relevant Documentation:
  • Work with Delta Lake table history - Time travel and table versioning
  • Use Delta Lake change data feed on Databricks - Change tracking capabilities
  • Delta Lake feature compatibility and protocols - Understanding Delta protocols

Table Types and Persistence

• Relevant Documentation:
  • Tutorial: Delta Lake - Creating managed and unmanaged tables
  • What is Delta Lake in Databricks? - Table metadata and management

Database and Table Operations

• Relevant Documentation:
  • SQL language reference - DDL operations for databases and tables
  • Tutorial: Delta Lake - Create, drop, rename operations

Data Explorer and Security

• Relevant Documentation:
  • Write queries and explore data in the SQL editor - Data Explorer functionality for exploring and securing data

PII Data Considerations

• Relevant Documentation:
  • What is a data lakehouse? - Data governance considerations including PII

Section 3: SQL in the Lakehouse

Query Operations and SELECT Statements

• Relevant Documentation:
  • SQL language reference - Complete SQL syntax reference
  • Query data - Query fundamentals

Data Modification Operations (MERGE INTO, INSERT, COPY INTO)

• Relevant Documentation:
  • Tutorial: Delta Lake - MERGE INTO operations and examples
  • Get started using COPY INTO to load data - COPY INTO vs other operations
  • Common data loading patterns using COPY INTO - Advanced COPY INTO patterns

JOINs and Subqueries

• Relevant Documentation:
  • SQL language reference - JOIN syntax and subquery patterns

Aggregation and Advanced SQL Features

• Relevant Documentation:
  • Aggregate data on Databricks - Aggregation fundamentals
  • GROUP BY clause - GROUP BY with CUBE and ROLLUP
  • Window functions - Windowing for time-based aggregation

Nested Data and Complex Types

• Relevant Documentation:
  • SQL language reference - Complex data type handling

Higher-Order Spark SQL Functions

• Relevant Documentation:
  • Higher-order functions - Performance optimization with higher-order functions
  • Higher-order functions - Working with arrays and complex types

User-Defined Functions (UDFs)

• Relevant Documentation:
  • What are user-defined functions (UDFs)? - UDF overview and best practices
  • User-defined functions (UDFs) in Unity Catalog - Unity Catalog UDF creation
  • CREATE FUNCTION (SQL and Python) - UDF creation syntax

Query Optimization and Performance

• Relevant Documentation:
  • Query data - Query optimization fundamentals
  • Best practices: Delta Lake - Performance optimization strategies

Section 4: Data Visualization and Dashboarding

Basic Visualizations in Databricks SQL

• Relevant Documentation:
  • Dashboards - Complete dashboard and visualization guide
  • Table visualizations - Specific visualization types and formatting

Visualization Types and Formatting

• Relevant Documentation:
  • Dashboards - Different visualization types (table, details, counter, pivot)
  • Table visualizations - Customization and formatting options

Dashboard Creation and Management

• Relevant Documentation:
  • Dashboards - Creating dashboards from multiple queries
  • Write queries and explore data in the SQL editor - Query management for dashboards

Dashboard Parameters and Interactivity

• Relevant Documentation:
  • Dashboards - Query parameters and dashboard-level parameters
  • Table visualizations - Interactive table features

Dashboard Sharing and Permissions

• Relevant Documentation:
  • Dashboards - Sharing dashboards and managing permissions
  • SQL warehouse access control - Access control for underlying compute

Refresh Schedules and Alerts

• Relevant Documentation:
  • Dashboards - Configuring refresh schedules
  • Write queries and explore data in the SQL editor - Query scheduling and alerts

Section 5: Analytics Applications

Statistical Analysis

• Relevant Documentation:
  • Aggregate data on Databricks - Statistical aggregations and analysis
  • SQL language reference - Statistical functions

Data Enhancement and Blending

• Relevant Documentation:
  • What is the medallion lakehouse architecture? - Data enhancement through the medallion architecture
  • Get started: Enhance and cleanse data - Practical data enhancement example

Last-Mile ETL

• Relevant Documentation:
  • Tutorial: Delta Lake - Data transformation examples
  • Common data loading patterns using COPY INTO - Data loading and transformation patterns

Additional Resources

Architecture and Best Practices

• Relevant Documentation:
  • Databricks architecture overview - Understanding the platform architecture
  • Lakehouse reference architectures - Reference architectures and patterns
  • Best practices for reliability - Reliability best practices

Data Import and Management

• Relevant Documentation:
  • Upload files to Databricks - Various file upload options
  • Recommendations for files in volumes and workspace files - File storage recommendations

API and Automation

• Relevant Documentation:
  • Statement Execution API: Run SQL on warehouses - Programmatic SQL execution
  • SQL Warehouses API - Warehouse management API

Exam Preparation Tips

1. Focus on Hands-On Practice: Most exam objectives require practical knowledge. Use the tutorial links to practice creating tables, writing queries, and building dashboards.

2. Understand the Medallion Architecture: This is a key concept that appears throughout the exam. Know the purpose of bronze, silver, and gold layers.

3. Master SQL Warehouse Configuration: Understand the differences between serverless, pro, and classic warehouses, including their performance characteristics and limitations.

4. Practice Data Loading: Be comfortable with COPY INTO, file uploads, and different data ingestion patterns.

5. Know Visualization Best Practices: Understand when to use different visualization types and how to format them effectively.

6. Study UDF Creation: Know how to create and apply user-defined functions in common scenarios.

7. Understand Partner Connect: Know how to integrate with BI tools like Tableau and Power BI.

Remember to practice with real data and scenarios similar to those you might encounter in a business environment. The exam focuses on practical application of Databricks SQL for data analysis tasks.