Data engineering in traditional environments often struggles with scalability, flexibility, and cost-efficiency. In this course, “Data Engineering in the Cloud,” you’ll gain the ability to design, deploy, and manage scalable and efficient data solutions in the cloud. First, you’ll explore the foundational cloud computing concepts relevant to data engineering, including the comparative strengths and weaknesses of major cloud platforms like AWS, Azure, and Google Cloud. Next, you’ll discover how to leverage these platforms to build robust data storage and processing architectures, utilizing services such as Amazon S3, Azure Blob Storage, Google Cloud Storage, and others for optimal data management. Finally, you’ll learn how to implement and optimize data pipelines in the cloud, focusing on cost management, security, and compliance to ensure that your data solutions are not only efficient but also secure and compliant with relevant regulations. When you’re finished with this course, you’ll have the skills and knowledge of cloud-based data engineering needed to architect and maintain cutting-edge data solutions that can scale dynamically with organizational needs.
Author Name: Bogdan Sucaciu
Author Description:
Software Engineer by day, Pluralsight author by night, Bogdan likes to experiment with cutting-edge technologies and teach about them. His favorite talking subjects are streaming data, event-driven architectures, distributed systems, and cloud technologies. He has several years of experience “cooking” software with JVM based languages, some flavors of web technologies, and garnishing with automated testing. He holds a BS in Robotics where he spent countless hours programming microcontrollers an… more

Table of Contents

• Overview
  1min
• Understanding Cloud Platforms and Services
  28mins
• Designing and Deploying Data Engineering Solutions
  9mins
• Optimizing Cloud Data Engineering Environments
  9mins