Data Engineering with Snowflake and AWS

About Data Engineering with Snowflake and AWS

Snowflake course for data engineers

This comprehensive Snowflake course is designed for data engineers who want to improve their ability to efficiently and scalably manage data in the cloud. With a hands-on focus, participants will be guided from the basics to advanced concepts of the Snowflake platform, which provides a modern and fully managed data warehouse architecture.

Benefits of using Snowflake for data engineering:

Elastic scalability: one of the key benefits of Snowflake is its cloud data storage architecture, which allows for elastic scalability. This means that data engineers can easily scale resources on demand to efficiently handle variable workloads and ensure consistent performance regardless of data volume.

Simplified data sharing: Snowflake offers a unique approach to sharing data across departments and teams. Using the concept of secure and controlled data sharing, data engineers can create a single data source that promotes efficient collaboration and consistent data analysis across the organisation.

Seamless integration with analytics tools: Snowflake is designed to integrate seamlessly with a variety of data analytics tools, allowing data engineers to create complete ecosystems for advanced data analysis. Compatibility with standard SQL makes it easy to migrate to the platform, while interoperability with popular tools such as Tableau and Power BI expands options for data visualisation and exploration.

In this course we deal with:

Snowflake basics

Platform architecture

Virtual warehouses - the clusters

Working with semi-structured data

Integrating Snowflake with AWS

Using Stages, Storage Integration, and Snowpipes

Using AWS S3, SQS, IAM

Automatic ingestion of data in near real time