AI/BI for Data Analysts

This course teaches data analysts how to design, build, publish, and operate AI/BI Dashboards in Databricks. AI/BI Dashboards combine governed Unity Catalog data with interactive visualizations, filters, and Genie integration so business users can explore answers without writing code.

The course follows a single end-to-end build. You start with source tables in Unity Catalog and finish with a published, monitored multi-page dashboard. Along the way you learn how dashboards fit into the broader Databricks AI/BI product family and where Genie, datasets, visualizations, and filters each fit in the workflow.

The content covers:

• AI/BI Dashboard fundamentals and how they relate to Genie and the rest of the Databricks platform.

• Exploring source data in Unity Catalog and designing reusable dashboard datasets with SQL.

• Authoring visualizations (KPIs, trends, breakdowns) and laying out a clean multi-page dashboard.

• Using Genie Code to draft SQL, charts, and filters from natural language prompts.

• Adding filters to make dashboards interactive and responsive to viewer questions.

• Publishing, sharing, and managing permissions so the right people can view and edit the dashboard.

• Running the dashboard in production with scheduled refresh, caching, and usage monitoring.

Note: For SCORM lecture files, please ensure that you close the SCORM window after completing the content. Do not click the ‘Next Lesson’ button, as doing so may prevent the SCORM module from being marked as complete.

Skill Level

Associate

Duration

Prerequisites

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

• Basic familiarity with the Databricks workspace. You can navigate the workspace UI, open and use notebooks, and attach a SQL warehouse or other compute resource.

• Basic familiarity with Unity Catalog. You understand the three-level namespace (catalog, schema, table) and can find a table in the catalog explorer.

• Working knowledge of SQL, including joins. You can read and write SELECT statements with WHERE, GROUP BY, and aggregates, and you can join two tables on a shared key.

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Upcoming Public Classes

Databricks Get Started Days (Data Engineering + Generative AI)

Get Started with Databricks for Data Engineering

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters, and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.

Get Started with Databricks for Generative AI

This course offers a practical introduction to the Mosaic AI platform, focusing on its key components and features for building and deploying generative AI systems. Participants will learn how Databricks facilitates the development of scalable generative AI solutions and explore Mosaic AI tools such as Vector Search, the Agent Framework, and MLflow’s generative AI capabilities for model tracking and logging. This course includes hands-on experience in constructing and evaluating Retrieval-Augmented Generation (RAG) pipelines, deploying generative AI agents, and leveraging evaluation frameworks to optimize performance. By the end of the course, learners will be equipped with the skills to design, deploy, and monitor common generative AI applications using Mosaic AI.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

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Databricks Get Started Days (Lakehouse Architecture + Data Warehousing)

Get Started with Lakehouse Architecture on Databricks

In this course, you will explore the Databricks Data Intelligence Platform from the perspective of platform architecture, specifically related to the platform foundation in lakehouse architecture. You will learn about the scope, vision, and capabilities of a platform founded in lakehouse architecture, with a focus on how Databricks integrates with a cloud platform’s architecture. You’ll learn about the key features of a successful lakehouse implementation, specifically how to adhere to the well-architected lakehouse framework, which emphasizes structural excellence through specific dimensions, principles and best practices. You’ll also learn about data architecture strategy for the acceleration of data and AI endeavors.

Get Started with Databricks for Data Warehousing

This course provides a comprehensive overview of Databricks’ modern approach to data warehousing, highlighting how a data lakehouse architecture combines the strengths of traditional data warehouses with the flexibility and scalability of the cloud. You’ll learn about the AI-driven features that enhance data transformation and analysis on the Databricks Data Intelligence Platform. Designed for data warehousing practitioners, this course provides you with the foundational information needed to begin building and managing high-performant, AI-powered data warehouses on Databricks.

This course is designed for those starting out in data warehousing and those who would like to execute data warehousing workloads on Databricks. Participants may also include data warehousing practitioners who are familiar with traditional data warehousing techniques and concepts and are looking to expand their understanding of how data warehousing workloads are executed on Databricks.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Free

instructor-led

Onboarding

Databricks Get Started Days (Data Engineering + Machine Learning)

Get Started with Databricks for Data Engineering

Get Started with Databricks for Machine Learning

In this course, you will develop the foundational skills needed to use the Databricks Data Intelligence Platform for executing basic machine learning workflows and supporting data science workloads. You will explore the platform from the perspective of a machine learning practitioner, covering topics such as feature engineering with Databricks Notebooks and model lifecycle tracking with MLflow. Additionally, you will learn about real-time model inference with Mosaic AI Model Serving and experience Databricks’ “glass box” approach to model development through AutoML. The course includes three instructor-led demonstrations, culminating in a comprehensive lab that reinforces the concepts covered in the demos.

You can create a Databricks Free Edition account and try the follow-along demos in a hands-on environment.

Free

instructor-led

Onboarding