Get Started with Databricks Platform Administration

In this course, you will learn the basics of platform administration on the Databricks Data Intelligence Platform. It offers a comprehensive overview of the Unity Catalog, a vital component for effective data governance within Databricks environments. Divided into five modules, it begins with a detailed introduction to Databricks infrastructure and its data intelligence platform, including an in-depth walkthrough of the Databricks Workspace. You will explore data governance principles within Unity Catalog, covering its key concepts, architecture, and roles. The course further emphasizes managing Unity Catalog metastores and compute resources, including clusters and SQL warehouses. Finally, you'll master data access control by learning about privileges, fine-grained access, and how to govern data objects. By the end, you will be equipped with essential skills to administer the Unity Catalog to implement effective data governance, optimize compute resources, and enforce robust data security strategies.

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

Skill Level

Onboarding

Duration

Prerequisites

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

• Familiarity with the Databricks Data Intelligence Platform and basic workspace operations (create clusters, run code in notebooks, use basic notebook operations)

• Basic understanding of identity and access management concepts (users, groups, service principals, authentication, authorization)

• Understanding of Unity Catalog fundamentals including the hierarchical object model (metastore, catalogs, schemas, tables, volumes, models)

• Basic knowledge of data governance principles and access control concepts (permissions, entitlements, administrative responsibilities)

• Beginner familiarity with cloud computing concepts (virtual machines, object storage, identity management, cloud resources)

• Basic understanding of workspace administration concepts including user management and permission assignment

• Knowledge of account-level versus workspace-level administration and the relationship between them

• A basic understanding of cloud computing and SQL concepts, including networking, SQL queries, and database structures such as tables and views

• Familiarity with Python programming, the Jupyter notebook interface, and foundational PySpark operations

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

Preparing for Databricks Certification Exams

Welcome to this course on preparing for your Databricks Certification exam. While most of the information found within this course is available on the Databricks Certification website, this training seeks to summarize that content to simplify your preparation.

Please note that this course will not teach any of the content on any particular exam.

Instead, this course will review the general information necessary for your test-taking experience to go as smoothly as possible, and point you to resources you can use to study for each exam.

Free

20m

Introductory

Databricks Get Started Days (Lakebase + AI Agents)

Get Started with Lakebase

This get started course introduces Databricks Lakebase, a fully managed PostgreSQL service built into the Databricks Data Intelligence Platform that brings operational (OLTP) and analytical (OLAP) workloads closer together.

The course begins with a conceptual lecture that compares OLTP and OLAP systems, explaining their different performance characteristics, storage models, and typical use cases. You will also explore the challenges organizations face when maintaining separate transactional databases and analytical platforms, including data movement, latency, and architectural complexity.

You will then learn how Databricks Lakebase helps address these challenges by providing a PostgreSQL-compatible operational database that integrates directly with the Databricks Lakehouse, enabling operational applications and analytics to work together within a unified platform.

This is a Get Started course, so the focus is on understanding the core concepts and basic workflows for working with Lakebase. Building full production applications on top of Lakebase is outside the scope of this course.

By the end of the course, you will understand how Lakebase enables organizations to bridge operational systems and analytics within a single governed platform powered by Unity Catalog and the Databricks Lakehouse.

Get Started with AI Agents on Databricks

This course is an introduction to AI agents, their role in modern AI applications, and how to build AI agent applications on the Databricks platform. You'll learn about the principles of AI agents, how they differ from traditional AI systems, and explore their key components. Through interactive demos and hands-on labs, you'll see how to build, deploy, and evaluate AI agents on Databricks using Databricks AI and Agent Bricks. By the end of this course, you'll understand how to create and deploy AI agents using the Databricks Data + AI Platform.

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

Free

instructor-led

Onboarding

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.

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.

Languages Available: English | 日本語 | 한국어

Free

Associate