Get Started with Databricks for Data Engineering
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Data Engineering
On-Site, Virtual
1 day
In this course, you will learn basic skills that will allow you to use the Databricks Data Intelligence Platform to perform a simple data engineering workflow and support data warehousing endeavors. You will be given a tour of the workspace and be shown how to work with objects in Databricks such as catalogs, schemas, volumes, tables, compute clusters and notebooks. You will then follow a basic data engineering workflow to perform tasks such as creating and working with tables, ingesting data into Delta Lake, transforming data through the medallion architecture, and using Databricks Workflows to orchestrate data engineering tasks. You’ll also learn how Databricks supports data warehousing needs through the use of Databricks SQL, Delta Live Tables, and Unity Catalog. With the purchase of a Databricks Labs subscription, the course also closes out with a comprehensive lab exercise to practice what you’ve learned in a live Databricks Workspace environment.
Objectives
By the end of this course, you'll be able to:
- Describe the available compute options for workloads performed on the Databricks Data Intelligence Platform.
- List the products and features Databricks offers for different data-centric needs within the Databricks Platform.
- Navigate the Databricks Workspace UI.
- Describe the core concepts, architecture, and benefits of Delta Lake.
- Apply various techniques for ingesting data into Delta Lake.
- Describe the Medallion Architecture for data transformation in Databricks.
- Describe how Delta Live Tables and Workflows facilitate unified orchestration in Databricks.
Prerequisites
- A basic understanding of data engineering principles and topics such as data collection, extraction, ingestion, and transformation.
