Build a conversational data assistant, Part 2 – Embedding generative business intelligence with Amazon Q in QuickSight
Machine Learning Blog
This article discusses Part 2 of building a conversational data assistant using Amazon Q in QuickSight, focusing on embedding generative business intelligence for the Amazon Worldwide Returns & ReCommerce (WWRR) organization.
- Extends the Returns & ReCommerce Data Assist (RRDA) solution to provide visual analytics through natural language queries
- Uses intent and domain classification to route queries to appropriate visualization pathways
- Implements intelligent Q topic retrieval and selection using Amazon Bedrock Knowledge Bases
- Develops a question rephrasing system to optimize queries for Amazon Q in QuickSight
- Embeds interactive visualizations directly within the chat interface
Key best practices include using AI to anticipate analytical needs, creating automatic translation layers between AI systems, and maintaining domain context across different data interaction modes. The solution aims to democratize data access by transforming natural language into both SQL queries and data visualizations.
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