Genie for Business Users

In this course, you will learn how to use Databricks AI/BI Genie to interact with your organization's data using natural language. As a business user, you will learn how to locate and access Genie spaces, ask effective data questions using the SPARK framework, validate and interpret Genie responses, generate visualizations from results, provide feedback to Genie space administrators, and share insights with colleagues. This course covers both standard Genie interactions and Genie Agent Mode for deeper exploratory analysis, empowering business users to go beyond static dashboards and get self-service answers from governed, secure data.

Skill Level

Onboarding

Duration

1h 30m

Prerequisites

The content was developed for participants with these skills/knowledge/abilities:

• Basic familiarity with data concepts (tables, columns, metrics).

• No SQL or coding knowledge required.

• Prior experience or basic familiarity with the Databricks workspace UI or Databricks One is helpful but not required.

• A basic understanding of business intelligence concepts such as dashboards and KPIs.

Public Class Registration

If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.

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Private Class Request

If your company is interested in private training, please submit a request.

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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

Building ETL Pipelines with SQL

This course teaches how to build production-ready ETL pipelines using pure SQL on the Databricks Data Intelligence Platform. Students learn Streaming Tables with Auto Loader for incremental ingestion, Materialized Views with incremental refresh for Silver-to-Gold transformations, AUTO CDC (FLOW AUTO CDC) for declarative SCD Type 1 and Type 2 dimension management, and Lakeflow Jobs with SQL File tasks for production orchestration. The course follows a realistic retail dataset through the medallion architecture (Bronze → Silver → Gold).

Note: Databricks Academy is transitioning to a notebook-based format for classroom sessions within the Databricks environment, discontinuing the use of slide decks for lectures. You can access the lecture notebooks in the Vocareum lab environment.

Building Reliable Conversational Agents with Genie

This course teaches you how to design, build, and maintain a Databricks Genie Space, a natural language interface that enables business users to ask questions about governed data and receive SQL-backed answers without writing code.

You will learn how Genie fits into the Databricks AI/BI product family and how it translates natural language into reliable SQL queries. The course focuses on what it takes to create a Genie Space that delivers accurate, consistent, and trustworthy results.

You will follow a complete end-to-end workflow, from understanding source data and defining benchmarks to configuring and refining a Genie Space using the full set of Knowledge Store curation tools. These include metadata, synonyms, prompt matching, SQL logic, example queries, and text instructions.

You will also learn how to share Genie Spaces with business users through Databricks One, understand how Unity Catalog governance is automatically enforced, and use monitoring and user feedback to continuously improve quality over time.

By the end of the course, you will be able to create and manage a production-ready Genie Space that delivers governed, self-service conversational analytics at scale.

Apache Spark Developer

Introduction to Apache Spark™

This course offers essential knowledge of Apache Spark, with a focus on its distributed architecture and practical applications for large-scale data processing. Participants will explore programming frameworks, learn the Spark DataFrame API, and develop skills for reading, writing, and transforming data using Python-based Spark workflows.

Languages Available: English | 日本語 | 한국어