Data Modeling Strategies

In this course, you will learn how to design scalable, analytics-ready data models using the Databricks Lakehouse Platform. The course is structured into three modules covering foundational data modeling principles, advanced warehousing and machine learning use cases, and modern data product design. You’ll explore core methodologies like Inmon’s CIF, Kimball’s dimensional modeling, and Data Vault 2.0, along with practical demos on implementing these strategies in Databricks.

Through hands-on labs, you’ll build ER diagrams, apply SCD Type 2 transformations, and create feature stores for ML workflows. The course also introduces the concept of data products and how product thinking, governance, and semantic consistency enable scalable cross-domain integration. By the end of the course, you’ll be equipped to model, manage, and operationalize data effectively in a unified Lakehouse architecture.

Note: The course includes practice labs that the learners should perform after going through the entire course.

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

Skill Level

Associate

Duration

Prerequisites

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

• Basic knowledge of data warehousing concepts, including schemas, ETL processes, and business intelligence workflows.

• Familiarity with SQL, including table creation, joins, constraints, and data manipulation using queries.

• Basic experience with Databricks or similar cloud-based data platforms.

• Fundamental knowledge of Lakehouse architecture and Delta Lake operations.

• Exposure to Python and PySpark for data processing and transformation tasks (recommended but not mandatory).

Self-Paced

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

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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

Architecting Data Warehouses for Large-Scale Deployments

This course covers performance optimization, cost control, and security for large-scale data warehousing deployments.This course is designed for Data Warehousing practitioners responsible for managing Databricks environments serving hundreds or thousands of users across multiple business units. You will gain the skills necessary to efficiently scale data warehousing operations while maintaining high performance, cost-effectiveness, and compliance with security standards.

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.

Paid & Subscription

Lab

Associate

Data Warehousing Practitioner

Data Warehousing with Databricks

This course is designed for data professionals who want to explore the data warehousing capabilities of Databricks. Assuming no prior knowledge of Databricks, it provides an introduction to leveraging Databricks as a modern cloud-based data warehousing solution. Learners will explore how use the Databricks Data Intelligence Platform to ingest, transform, govern, and analyze data efficiently using the industry-standard TCP-DI dataset as a reference. Learners will also explore Genie, an innovative Databricks feature that simplifies data exploration through natural language queries. By the end of this course, participants will be equipped with the foundational skills to implement and optimize a data warehouse using Databricks.

Note: Databricks Academy is transitioning from video lectures to a more streamlined PDF format with slides and notes for all self-paced courses. Please note that demo videos will still be available in their original format. We would love to hear your thoughts on this change, so please share your feedback through the course survey at the end. Thank you for being a part of our learning community!

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

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 using available templates. Next, you will learn how to build and deploy a data-driven application that integrates with other platform features. The course then covers how to set up an IDE for Databricks Apps, and how to edit and deploy an app using an IDE. It concludes with how to implement security and best practices for an enterprise app.

Paid & Subscription

Lab

Associate