Semi-structured Data: Loading and Querying JSON & XML Data in Snowflake
Snowflake | Intermediate
- 11 videos | 1h 19m 32s
- Includes Assessment
- Earns a Badge
Structured data follows a fixed schema, usually does not contain hierarchical information, and is typically stored in a tabular format. Alternatively, semi-structured data does not adhere to a fixed schema, supports hierarchical information, and offers schema flexibility and standardization. The Snowflake platform offers support for structured and semi-structured data. In this course, learn how to load JSON and XML data in Snowflake tables and examine Snowflake's OBJECT, ARRAY, and VARIANT types. Next, explore data validation, how you can handle source data errors in a load process, and how to query JSON structures in Snowflake. Finally, practice loading and querying XML data, including using Snowflake functions. Upon completion, you'll be able to work with JSON and XML data in Snowflake.
WHAT YOU WILL LEARN
Discover the key concepts covered in this courseRecall how structured and semi-structured data workSet up a table and internal snowflake stage and load json data into the stageAccess unstructured json data from snowflakeLoad json data as arrays into snowflake tablesExtract column values from json data and load them into a regular snowflake table
Perform load operations with various configurations and file patternsRemove unnamed outer arrays from json data when loading into snowflakeExecute queries on json data containing nested structuresQuery xml data and flatten out hierarchical dataSummarize the key concepts covered in this course
IN THIS COURSE
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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