[UDM] Data Engineering with Snowflake and AWS Course (Apr 2024) + Resources

Master Modern Data Engineering with Snowflake and AWS
Enter the realm of data engineering in the clouds and gain experience in developing, creating, and supporting scalable data pipelines with Snowflake and AWS. The Data Engineering with Snowflake and AWS Course will show you how to combine the scalability of Snowflake data warehouse with the capabilities of AWS services to build effective, real-time information processes. You will learn to turn unstructured data into insights and answers, starting with the fundamentals of Snowflake architecture and its sophisticated automation methods.

Build Strong Foundations and Hands-On Experience
You will start by learning the basics about Snowflake, its virtual warehouses, data storage model, and query processing engine. You will then jump into practical uses such as structured and semi-structured data, configuring storage integrations, and configuring data ingestion pipelines. You will also learn how to seamlessly connect Snowflake with the AWS services, including S3, IAM, and SNS, to ensure secure and scalable data management across platforms.

Design End-to-End Data Pipelines and Automate Workflows
The Data Engineering with Snowflake and AWS Course will teach you how to create complete pipelines of ETL and ELT entirely. You will learn to extract, transform, and load data effectively and utilise tools such as Snowpipe to load data in near real time. You’ll also learn over the course of step-by-step examples to automate workflows and control the data flow between Snowflake and AWS, allowing you to work with large datasets with confidence and accuracy.

Learn from Real-World Scenarios and Industry Practices
Developed to help future data engineers, analysts, or cloud professionals succeed in data-driven careers, this course offers both the technical and architectural expertise to succeed in such roles. At the conclusion, you will be well versed in Snowflake and AWS integration, know how to build best practices in scalability and security, and can create production-ready data pipelines that drive modern analytics and business intelligence.