Catalog Management and Data Organization

In this course, you will learn how to design, implement, and govern catalog structures and large-scale data organization on the Databricks Data Intelligence Platform. It offers a comprehensive view of Unity Catalog as the centralized governance layer for an enterprise lakehouse. Divided into five modules, it begins by placing Unity Catalog within the cloud deployment model — covering the Account Console, metastore creation, and the administrator role hierarchy. You will then translate organizational topology (business units, regions, and dev/QA/prod environments) into a scalable catalog and schema design using naming conventions, ownership patterns, and MANAGE delegation. The course then covers secure storage integration with storage credentials, external locations, the managed-storage hierarchy, managed versus external tables, and UC Volumes for non-tabular data. Next, you will apply access patterns and isolation strategies — the three-level GRANT chain, workspace-catalog binding, and schema-level Attribute-Based Access Control (ABAC) policies — to enforce fine-grained data protection at scale. Finally, the course closes with best practices for catalog design, automation, least-privilege permissions, and group-based access management.

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

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

• Familiarity with the Databricks Data Intelligence Platform and basic workspace operations (creating clusters and SQL warehouses, running SQL and Python in notebooks, basic notebook navigation)

• Working knowledge of Unity Catalog fundamentals, including the three-level namespace (metastore → catalog → schema → table) and the core securable objects (tables, views, volumes, models)

• Hands-on experience with Unity Catalog–enabled workspaces, including creating and managing catalogs, schemas, and tables via SQL

• Solid understanding of identity and access management concepts (users, groups, service principals, authentication, authorization) and the difference between account-level and workspace-level administration

• Working knowledge of data governance principles — access control, data classification, compliance, and audit — and how they map to platform features

• Familiarity with cloud object storage concepts (S3, ADLS, or GCS), including IAM roles, bucket-level paths, and the role of storage credentials in cross-service access

• Introductory familiarity with Delta Lake (managed vs external tables, Delta lifecycle) and Lakeflow for orchestrating data workflows

• Practical experience with enterprise architecture in larger organizations — multi-business-unit topology, regional data residency, and dev/QA/prod environment separation

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Upcoming Public Classes

Data Engineer

Automated Deployment with Declarative Automation Bundles

This course provides a comprehensive review of DevOps principles and their application to Databricks projects. It begins with an overview of core DevOps, DataOps, continuous integration (CI), continuous deployment (CD), and testing, and explores how these principles can be applied to data engineering pipelines.

The course then focuses on continuous deployment within the CI/CD process, examining tools like the Databricks REST API, SDK, and CLI for project deployment. You will learn about Declarative Automation Bundles (DABs) and how they fit into the CI/CD process. You’ll dive into their key components, folder structure, and how they streamline deployment across various target environments in Databricks. You will also learn how to add variables, modify, validate, deploy, and execute Declarative Automation Bundles for multiple environments with different configurations using the Databricks CLI.

Finally, the course introduces Visual Studio Code as an Interactive Development Environment (IDE) for building, testing, and deploying Declarative Automation Bundles locally, optimizing your development process. The course concludes with an introduction to automating deployment pipelines using GitHub Actions to enhance the CI/CD workflow with Declarative Automation Bundles.

By the end of this course, you will be equipped to automate Databricks project deployments with Declarative Automation Bundles, improving efficiency through DevOps practices.

Note:

1. 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!

2. This course is the fourth in the 'Advanced Data Engineering with Databricks' series.

Languages Available: English | 日本語 | 한국어

Free

Professional

Data Warehousing Practitioner

Get Started with Databricks for Data Warehousing

This course provides a comprehensive, hands-on 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. Working end-to-end with a fictional retailer (Vintage Audio Co.), you will explore the workspace, query governed Unity Catalog tables, keep Delta tables fast for analytical reads, load data incrementally with Auto Loader, model a star schema, and deliver consistent insights through Unity Catalog metric views — all from a single, governed environment, with AI-driven features (Predictive Optimization, Genie Code) built in throughout.

Free

Onboarding

Agentic Application Fundamentals

AI has changed what developers are asked to build: agents, copilots and intelligent tools are moving from experiments into production, and the work is shifting from writing code to orchestrating models, data, and services. In this course, you'll learn how building agentic applications where the data lives removes the infrastructure overhead of stitching together fragmented stacks. Through a guided account-briefing demo, you'll see how Databricks Apps, Lakebase, and Agent Bricks (Genie Spaces, Knowledge Assistants and Supervisor Agents) work together on one governed, serverless foundation to deliver a production-ready agentic application.

Free

Introductory