Data Management and Governance with Unity Catalog

In this course, you'll learn about data management and governance using Databricks Unity Catalog. It covers foundational concepts of data governance, complexities in managing data lakes, Unity Catalog's architecture, security, administration, and advanced topics like fine-grained access control, data segregation, and privilege management.

Note: This course is part of the 'Data Engineering with Databricks' course series.

Skill Level

Associate

Duration

Prerequisites

Beginner familiarity with cloud computing concepts (virtual machines, object storage, etc.)
Intermediate experience with basic SQL concepts such as SQL commands, aggregate functions, filters and sorting, indexes, tables, and views.
Basic knowledge of Python programming, jupyter notebook interface, and PySpark fundamentals.

Self-Paced

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

See all our registration options

Registration options

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

Data Analyst

Get Started with SQL Analytics and BI on Databricks

Please note this is the latest version of the 'Get Started with Databricks for Data Analysis' course, which was released on November 12, 2024.

In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data analytics workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with data objects in Databricks such as catalogs, schemas, tables, compute clusters, notebooks, and dashboards. You will then follow a basic data analytics workflow to perform tasks such as manipulating data using Databricks SQL, leveraging Delta Lake version logs to time travel, creating dashboards within the platform, and creating Genie Spaces for data exploration using natural language prompts. You will also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog.

Free

Onboarding

Platform Architect

AWS Databricks Platform Architect Accreditation

Welcome to the AWS Databricks Platform Architect Accreditation

This is a 20-minute assessment that will test your knowledge about fundamental concepts related to Databricks platform administration on AWS. Questions will assess your knowledge about cloud-specific elements of the platform, including integration with managed services and security best practices.

After successfully completing this assessment, you will be awarded an AWS Databricks Platform Architect badge.

Courses to help you prepare for the Accreditation: AWS Databricks Platform Administration Fundamentals.AWS Databricks Networking and Security Fundamentals.AWS Databricks Cloud Integrations.Learning path This course is part of AWS Databricks Platform Architect Learning Plan.

Proof of completion Upon an 80% pass rate, you will receive a badge from Databricks.

Free

20m

Associate

Machine Learning Practitioner

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.

Free

instructor-led

Onboarding