Data Engineering with Databricks (Associate Level)

Overview

🕮 Off the shelf (OTS)

This course provides an introduction to data engineering with Databricks, covering key tools and frameworks such as Delta Lake, Databricks Workflows, Delta Live Tables, and Unity Catalog. Participants will learn how to ingest, transform, and manage data using Delta Lake, deploy workloads with Databricks Workflows, build efficient pipelines with Delta Live Tables, and apply data governance principles using Unity Catalog. The course includes hands-on labs and real-world applications to ensure learners develop practical skills for working with Databricks effectively.
This course prepares learners for the Associate Data Engineering certification exam and provides the foundational knowledge required to advance to the Advanced Data Engineering with Databricks course.

Participants should have:
• Beginner familiarity with basic cloud concepts (virtual machines, object storage, identity management).
• Ability to perform basic code development tasks (e.g., creating compute instances, running code in notebooks, using basic notebook operations, and importing repositories from Git).
• Intermediate familiarity with SQL, including commands such as CREATE, SELECT, INSERT, UPDATE, DELETE, GROUP BY, JOIN.
• Intermediate experience with SQL concepts such as aggregate functions, filters, sorting, indexes, tables, and views.
• Basic knowledge of Python programming, Jupyter Notebook interface, and PySpark fundamentals.

This course is designed for:
• Data Engineers who want to enhance their knowledge of Databricks and Delta Lake.
• Data Analysts looking to expand their expertise in data pipelines and transformation.
• Cloud Engineers and Developers working with big data frameworks.
• Professionals preparing for the Databricks Associate Data Engineering certification.

This course features:
• Interactive labs to apply concepts in a real-world Databricks environment.
• Guided exercises demonstrating how to configure and optimise Delta Lake, Workflows, and Unity Catalog.
• Real-world case studies showcasing best practices in data engineering with Databricks.
• Troubleshooting scenarios to develop problem-solving skills.