Data Analysis with Databricks

**Important Notice**: This course will be retired on May 19, 2025. It has been updated and is now offered as 2 modular courses:

1- SQL Analytics on Databricks

2- AI/BI for Data Analysts

Databricks recommends that you complete the course by May 19 or enroll in the free self-paced versions of these modules available in the ‘DB002 [FREE Self-Paced] Databricks Academy’ catalog. Please select one of the following links based on your role:

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This content provides a comprehensive introduction to Databricks SQL. It is designed with the intention of supporting individuals seeking the Associate Data Analysis of Databricks SQL certification. Participants will learn about ingesting data, writing queries, producing visualizations and dashboards, and how to connect Databricks SQL to additional tools by using Partner Connect.

Skill Level

Associate

Duration

Prerequisites

At a minimum, you should be familiar with the following before attempting to take this content:

General SQL fundamentals (e.g. write basic SELECT from statements)

Courses you should consider taking before taking this content include:

Databricks Lakehouse Fundamentals

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Registration options

Databricks has a delivery method for wherever you are on your learning journey

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Apache Spark Developer

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This course explores the Lakehouse architecture and Medallion design for scalable data workflows, focusing on Unity Catalog for secure data governance, access control, and lineage tracking. The curriculum includes building reliable, ACID-compliant pipelines with Delta Lake. You'll examine Spark optimization techniques, such as partitioning, caching, and query tuning, and learn performance monitoring, troubleshooting, and best practices for efficient data engineering and analytics to address real-world challenges.

Free

Associate

Apache Spark Developer

Developing Applications with Apache Spark™

Master scalable data processing with Apache Spark in this hands-on course. Learn to build efficient ETL pipelines, perform advanced analytics, and optimize distributed data transformations using Spark’s DataFrame API. Explore grouping, aggregation, joins, set operations, and window functions. Work with complex data types like arrays, maps, and structs while applying best practices for performance optimization.

Free

Associate

Apache Spark Developer

Stream Processing and Analysis with Apache Spark™

Learn the essentials of stream processing and analysis with Apache Spark in this course. Gain a solid understanding of stream processing fundamentals and develop applications using the Spark Structured Streaming API. Explore advanced techniques such as stream aggregation and window analysis to process real-time data efficiently. This course equips you with the skills to create scalable and fault-tolerant streaming applications for dynamic data environments.

Free

Associate