How to Load and Query Semi-Structured JSON Data from AWS S3 to Amazon Redshift

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📌 Video Description

In this hands-on lab, you will learn how to load and query semi-structured JSON data from an Amazon S3 bucket into an Amazon Redshift cluster. The video demonstrates modern data engineering techniques in Amazon Redshift for working with semi-structured data without complex flattening.

You will explore how to ingest JSON data into Redshift using the COPY command, store it using the SUPER data type, and efficiently query nested JSON structures using PartiQL. This approach is ideal for handling evolving schemas and large-scale analytical workloads.

🔍 What You Will Learn

How to load semi-structured JSON files from Amazon S3 to Amazon Redshift

Using the COPY command with JSON options (noshred / auto-shredding)

Understanding and using the SUPER data type in Amazon Redshift

Querying nested JSON data using PartiQL

Handling schema evolution in semi-structured data

Best practices for JSON ingestion and querying in Redshift

🛠 Services & Concepts Covered

Amazon Redshift

Amazon S3

Semi-Structured JSON Data

SUPER Data Type

PartiQL

Data Engineering on AWS

🎯 Who This Video Is For

Data Engineers

Cloud Engineers

AWS Developers

Analytics and BI Professionals

Anyone preparing for AWS analytics or data engineering interviews

🔔 Stay Connected

If you enjoy hands-on AWS labs without fluff, subscribe to the channel for more deep-dive tutorials on Amazon Redshift, AWS Glue, ETL pipelines, and modern data engineering on AWS.

Repo link : https://github.com/RekhuGopal/PythonH...

#amazonredshift
#awss3
#jsondata
#semistructureddata
#redshiftjson
#s3toredshift
#redshiftcopy
#copycommand

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