Skip to main content

Data Management and Governance with Unity Catalog

In this Data Governance with Unity Catalog session, you'll learn concepts and perform labs that showcase workflows using Unity Catalog - Databricks’ solution to data governance. We'll start off with a brief introduction to Unity Catalog, discuss fundamental data governance concepts, and then dive into a variety of topics including using Unity Catalog for data access control, managing external storage and tables, data segregation, and more. 


Note: This is the fourth course in the 'Data Engineering with Databricks' series.


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

Skill Level
Associate
Duration
2h
Prerequisites

- Familiarity with the Databricks Lakehouse completion (completion of the course Fundamentals of the Databricks Data Intelligence Platform V2)

- Basic knowledge of Python programming, jupyter notebook interface, and PySpark fundamentals.

- Familiarity with data governance topics

- 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.

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

Runtime

Self-Paced

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

Register now

Instructors

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

Register now

Learning

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

Purchase now

Scale

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 Engineer

Data Ingestion with Lakeflow Connect

This course provides a comprehensive introduction to Lakeflow Connect as a scalable and simplified solution for ingesting data into Databricks from a variety of data sources. You will begin by exploring the different types of connectors within Lakeflow Connect (Standard and Managed), learn about various ingestion techniques, including batch, incremental batch, and streaming, and then review the key benefits of Delta tables and the Medallion architecture.

From there, you will gain practical skills to efficiently ingest data from cloud object storage using Lakeflow Connect Standard Connectors with methods such as CREATE TABLE AS (CTAS), COPY INTO, and Auto Loader, along with the benefits and considerations of each approach. You will then learn how to append metadata columns to your bronze level tables during ingestion into the Databricks data intelligence platform. This is followed by working with the rescued data column, which handles records that don’t match the schema of your bronze table, including strategies for managing this rescued data.

The course also introduces techniques for ingesting and flattening semi-structured JSON data, as well as enterprise-grade data ingestion using Lakeflow Connect Managed Connectors.

Finally, learners will explore alternative ingestion strategies, including MERGE INTO operations and leveraging the Databricks Marketplace, equipping you with foundational knowledge to support modern data engineering ingestion.

Free
2h
Associate

Questions?

If you have any questions, please refer to our Frequently Asked Questions page.