Enabling natural language access to structured data using Amazon S3 Tables and Amazon Bedrock Knowledge Bases

This article demonstrates how to enable natural language querying of structured data by combining Amazon S3 Tables, Amazon Bedrock Knowledge Bases, and Amazon Redshift Serverless.

• S3 Tables with Apache Iceberg provide managed storage for structured data at scale
• Bedrock Knowledge Bases translate natural language questions into optimized SQL queries
• AWS Glue Data Catalog integration enables schema metadata access and federation
• Redshift Serverless executes queries against S3 Tables without operational overhead
• Lake Formation provides fine-grained permissions and governance for data access
• Business users query data conversationally without SQL expertise or waiting for technical teams
• Solution includes step-by-step setup: table bucket creation, Glue integration, Redshift configuration, Knowledge Base setup
• IAM authentication enables password-less Redshift access for Bedrock service roles
• Pattern extends to AWS managed S3 table buckets for read-only data access

This architecture enables faster decision-making, lower costs, broader data access, and stronger governance for organizations managing large volumes of structured data.