aws-samples/data-insights-with-amazon-q-business
Amazon Q Business enables querying structured data using natural language, leveraging schemas and metadata. This example demonstrates an architecture to query cost and usage data in Amazon Athena with Q Business. The solution can be extended to additional data sources with query validation and prompting techniques for broader use cases.
This project helps finance teams, operations managers, and business analysts understand their AWS spending using simple questions. You input natural language questions like "What were the top 3 services by spend last year?" and it outputs a table or chart showing the answer, based on your AWS cost and usage data. It's designed for anyone needing quick insights from structured data without writing complex queries.
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Use this if you need to quickly get answers from your AWS cost and usage data using everyday language, without needing to be a SQL expert.
Not ideal if your primary goal is to perform deep, ad-hoc data science analysis or if you need to integrate with non-AWS data sources without significant customization.
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Python
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MIT-0
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Last pushed
Nov 13, 2024
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