Semi-structured data is data that does not conform to the table structures employed by traditional relational SQL databases. This type of data can contain complex values – arrays, nested and other complex structures – that are often associated with serialization formats, such as JSON.
Amazon Redshift introduced the SUPER data type, a set of schemaless array and structure values, to support the persistence of semi-structured data in a schemaless form. This provides a rapid and flexible way to ingest semi-structured data, such as JSON data, and query it without having to impose a schema on or flattening the data.
SQL users tend to have difficulty working with semi-structured data sources because there is often no out-of-the-box SQL support, requiring the user to learn multiple complex functions and, in many instances, use third-party tools.
However, as you work with the data in Redshift and transform the data to get it ready for analytics, you will likely need to flatten that data for further transformations in Matillion ETL, and that is where our Extract Nested Data component comes to the rescue.
Get started on Matillion Academy
Learn how to work with the SUPER data type within Matillion ETL. This course will show you how to:
- Import SUPER Data Type Tables using:
- Start component
- Create Table component
- SQL Script component
- Work with SUPER Data Types using:
- Extract Nested data component to flatten the SUPER data
- A variety of other components to help visualise data better
Unlock the value of your semistructured data
Get started on Matillion Academy today and simplify the way you work with semistructured data in Amazon Redshift.