Data Interoperability with Unity Catalog

This course explores how to achieve seamless data interoperability between systems using Databricks Unity Catalog as a unified governance layer, using both Delta and Iceberg open table formats. Participants will learn to implement, manage and optimize a data environment where tables can be accessed by both Delta and Iceberg clients, enabling cross platform analytics and eliminating data silos.

Skill Level

Associate

Duration

Prerequisites

⇾ Basic understanding of the Lakehouse architecture

⇾ Basic familiarity with the Medallion architecture

⇾ Knowledge of UC fundamentals for governance

⇾ Familiarity with the design or development of ETL pipelines using Databricks

⇾ Basic SQL for querying and transforming data

Outline

⇾ Introduction to Data Interoperability

⇾ Working with Managed Tables in Unity Catalog

⇾ Use Cases for Data Interoperability

⇾ Best Practices for Interoperability

Upcoming Public Classes

Date	Time	Language	Price
Date	Time	Language	Price	Oct 16	01 PM - 05 PM (America/New_York)	English	$750.00

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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.

Data Modeling Strategies

This course offers a deep dive into designing data models within the Databricks Lakehouse environment, and understanding the data products lifecycle. Participants will learn to align business requirements with data organization and model design leveraging Delta Lake and Unity Catalog for defining data architectures, and techniques for data integration and sharing.

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

Data Warehousing Practitioner

SQL Programming and Procedural Logic

In this course, you will explore core SQL programming and procedural logic skills within Databricks, focusing on how to build modular, maintainable, and production-ready analytics workflows. You’ll start by learning about key SQL constructs—such as Common Table Expressions, temporary views, and User Defined Functions—that make your SQL development cleaner and more reusable. The course then guides you through advanced SQL scripting techniques using compound statements, variables, control flow, conditionals, loops, and robust error handling to create structured and flexible SQL processes. Finally, you’ll discover how to orchestrate and modernize complex workflows with Lakeflow Jobs and migration strategies, transforming legacy tasks into modular, automated pipelines that leverage the full capabilities of the Databricks platform.