Building Enterprise Applications with Databricks Apps

This course introduces Databricks Apps, a new feature that empowers developers to build and deploy secure data and AI applications directly on the Databricks platform. It is primarily designed for data scientists, data engineers, and developers who need to create custom applications that make data insights accessible to non-technical users within their organizations.

The course begins with an overview of the main components of Databricks Apps, followed by the deployment of a simple app that integrates with an external service. Next, you will learn how to build and deploy intelligent, data-driven applications that integrate with Databricks platform features. The course then covers how to develop apps outside the Databricks environment. It concludes with a detailed treatment of best practices for implementing secure and reliable enterprise apps.

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.

Skill Level

Associate

Duration

Prerequisites

In this course, the content was developed for participants with these skills/knowledge/abilities:

• Basic familiarity with Databricks workspace operations, including navigation, creating notebooks, running code, and accessing workspace features through the UI

• ntermediate experience with Python programming, including virtual environments, package management, and web application development concepts

• Understanding of integrated development environments (IDEs) such as VSCode or PyCharm, including project setup, debugging, and code execution

• Basic knowledge of Unity Catalog concepts, including catalogs, schemas, tables, and data governance principles for accessing data objects programmatically

• Familiarity with command line interfaces, particularly Databricks CLI installation, configuration, and authentication using personal access tokens

• Basic understanding of web application frameworks and concepts, including user interfaces, form handling, and client-server interactions

• Beginner experience with service principals, identity management, and authentication concepts within cloud computing environments

• Basic knowledge of application deployment concepts, including local development, testing, and production deployment workflows

Outline

1. Introduction to Databricks Apps

• Overview of Databricks Apps

• Demo: Building a Simple Databricks App

• Lab: Implementing Observability in a Databricks App

2. Building Intelligent Applicatons

• Anatomy of a Databricks App

• Demo: Building an Intelligent Data-driven App

• Lab: Making Intelligent Apps Context-Aware

3. Production Readiness

• Operational Best Practices

• Demo: Implementing Best Practices

• Demo: Vibe Coding an App

Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	Sep 01	01 PM - 05 PM (Europe/Paris)	-	English	$750.00
Oct 01	09 AM - 01 PM (Asia/Kolkata)	-	English	$750.00
Oct 01	01 PM - 05 PM (America/New_York)	-	English	$750.00

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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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Upcoming Public Classes

Date	Time	Your Local Time	Language	Price
Date	Time	Your Local Time	Language	Price	Sep 01	01 PM - 05 PM (Europe/Paris)	-	English	$750.00
Oct 01	09 AM - 01 PM (Asia/Kolkata)	-	English	$750.00
Oct 01	01 PM - 05 PM (America/New_York)	-	English	$750.00

Registration options

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Upcoming Public Classes

Data Architect

Data Modeling Strategies

This course walks practitioners through the full spectrum of data modelling approaches on the Databricks Data Intelligence Platform - from classical data warehouse techniques (Inmon, Kimball, Data Vault 2.0), through Feature Store-driven ML use cases, to productising data via Data Products on Unity Catalog.

Each modelling approach is introduced with a lecture, then reinforced with a hands-on demo against a shared dataset (TPC-H samples). The course finishes with a comprehensive end-to-end lab that exercises ERM, dimensional modelling, Data Vault 2.0, and the Feature Store in a single integrated workflow.

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.

Languages Available: English | 日本語 | Português BR | 한국어

Data Warehousing Practitioner

SQL Programming and Procedural Logic

In this course, you will explore core SQL programming and procedural logic skills within Databricks, focusing on how to build modular, maintainable, and production-ready analytics workflows. You’ll start by learning about key SQL constructs—such as Common Table Expressions (including advanced recursive CTEs), session-scoped objects like temporary views and tables, and User Defined Functions—that make your SQL development cleaner and more reusable. The course then guides you through advanced SQL scripting techniques using compound statements, variables, control flow, conditionals, loops, and robust error handling to create structured and flexible SQL processes. You will also learn how to guarantee data consistency across these multi-step pipelines using ACID-compliant multi-statement transactions. Finally, you’ll discover how to encapsulate logic into SQL Stored Procedures and orchestrate complex workflows with Lakeflow Jobs and migration strategies, transforming legacy tasks into modular, automated pipelines that leverage the full capabilities of the Databricks platform.

Data Warehousing Practitioner

Building Semantic Models in Databricks with UC Metric Views

In this course, you’ll learn how to empower your data consumers to get validated business insights with less burden on you and the rest of your enterprise's data and AI team. Through building a semantic layer on top of your gold layer, you'll offer decision makers and business analysts the opportunity to explore key business performance indicators in novel ways, while still maintaining efficient data operations and enterprise-vetted metrics.