Working with Semi-structured Data with Snowflake
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.
Table of contents
About the author
Warner is a SQL Server Certified Master, MVP, and Solutions Architect at Pythian, a global Canada-based company specializing in data and infrastructure services. A brief stint in .NET programming led to his early DBA formation, working for enterprise customers in Hewlett-Packard's ITO organization. From HP he transitioned to his current position at Pythian, managing multiple clients of different sizes and industries. He leads a highly-talented team of data professionals that keep things running ... more