Databricks Data Engineer Associate Certification Course: Data Engineering and Data Science on a Unified Platform

Databricks provides a unified platform for data engineering, data science, and machine learning. It integrates with popular big data technologies, allowing users to perform data processing, analytics, and machine learning tasks in a single environment. With the growing adoption of the Databricks platform over the last few years, obtaining the Databricks Data Engineer Associate certification can enhance data engineering skills, boost career prospects, and demonstrate a commitment to continuous learning and professional development in the field of data engineering.

This on-demand course helps learners prepare for the Databricks Certified Data Engineer Associate exam. Through a mix of concise presentations, demonstrations, and interactive assessment, the course thoroughly reviews the five domains of the exam: the Databricks Lakehouse platform, ELT with Apache Spark, incremental data processing, production pipelines, and data governance. Some of the topics within these domains that will be covered include lakehouse features, cluster management, table and view creation, data extraction and validation, Delta Lake ACID transactions, task management in Databricks Jobs, and the Unity Catalog. By the end of the course, learners will have the knowledge and skills necessary to pass this exam and become a certified Databricks Data Engineer Associate.

Next Steps: After completing this course, you can continue advancing your knowledge and skills by completing a course on the following topic(s)

• Databricks Data Engineer Associate Certification Prep in 2 Weeks (Live Event) by Derar Alhussein
• Data Lakehouse Fundamentals (Live Event) by Janani Ravi

What you’ll learn and how to apply it

• Perform fundamental data engineering tasks in Databricks, such as data loading, reading, manipulation, as well as basic Databricks pipeline operations

Module Learning Objectives

• Module 1: To be able to have a solid understanding of the Databricks Lakehouse architecture, including its administrative interface, compute, and storage components.
• Module 2: To be able to have a solid understanding of the ELT technologies involved in the Databricks ecosystem, such as basic SQL, function definitions, and JSON/Array processing.
• Module 3: To be able to utilize the incremental data processing technologies involved in the Databricks ecosystem, such as data loading, Medallion architecture, and data pipelines.
• Module 4: To be able to deploy the production pipelines involved in the Databricks ecosystem, especially the management of jobs and tasks.
• Module 5: To be able to utilize the data governance features involved in the Databricks ecosystem, such as data object privileges and Unity Catalog.

This course is for you because

• You are an entry level data engineer, data scientist, or ML engineer seeking to gain a fundamental understanding of data engineering tools offered by Databricks.
• You are looking to move into a new role that utilizes Databricks as a part of the solution, a role that favors or requires candidates with a Databricks Certified Data Engineer Associate certification.
• You’re an established data engineer, data scientist, or ML engineer looking to understand this technology better and the ways it can benefit your own workflow.

Prerequisites

• Beginner level knowledge of standard SQL, Python, and Spark
• Beginner level knowledge of cloud computing
• Beginner level knowledge of Databricks