Amazon Quick introduces Dataset Q&A for conversational analytics against enterprise data

Amazon Quick Dataset Q&A Release

Amazon Quick now supports Dataset Q&A, a conversational analytics capability that allows users to ask natural language questions directly against their enterprise data. This feature, alongside Dashboard Q&A, provides a new way to interact with data in Amazon Quick, enabling users to explore their data and get actionable insights using natural language, while adhering to governance rules.

Dataset Q&A is powered by Amazon Quick's text-to-SQL agent, which interprets user questions, identifies the right data, and generates precise SQL. It works across various data sources, generating optimized SQL for SPICE or AWS data assets such as Amazon Redshift, Amazon Athena, Aurora PostgreSQL, and Apache Iceberg tables stored in Amazon S3.

Data owners can enrich datasets with custom instructions, business definitions, and field descriptions directly in Amazon Quick or through file uploads. These curated semantics, along with dataset metadata, are ingested into a knowledge graph that captures the meaning and relationships across data assets, enabling accurate dataset identification and SQL generation.

The Dataset Q&A agent delivers accurate answers for a range of question types, from trend analysis to multi-condition analytical queries. It also includes an Explain capability, allowing users to inspect the reasoning behind each answer and validate the generated SQL.

What to do

• Explore Dataset Q&A in Amazon Quick.
• Enrich your datasets with custom instructions and definitions.
• Validate the generated SQL for accuracy.

Source: AWS release notes

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