Expanded Library

Working with Semi-structured Data with Snowflake

by Warner Chaves

Snowflake offers full support for semi-structured data. This course will teach you how to apply schema on read, loading, and writing to semi-structured file formats, working with the variant data type to interpret semi-structured fields and more.

What you'll learn

The Snowflake Cloud Data Platform has full support for semi-structured data stored in formats such as JSON, XML, parquet, and more. In this course, Working with Semi-structured Data with Snowflake, you’ll learn to load, write, and query these data formats that are very common in data engineering projects.

First, you’ll explore Snowflake’s supported semi-structured file formats and the powerful and flexible variant data type. Next, you’ll discover how to load and write in popular formats such as JSON, parquet, and more. Finally, you’ll learn how to use Snowflake’s SQL implementation and built-in functions for querying semi-structured data.

When you’re finished with this course, you’ll have the skills and knowledge of working with semi-structured data to apply on your next data engineering project.

About the author

Warner is a SQL Server Certified Master, MVP, and Principal Consultant at Pythian. He manages clients in many industries and leads a talented team that maintains and innovates with their data solutions. When he's not working in Ottawa, Ontario, he can be found in his home country of Costa Rica.

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