Talk to Your Data: Query Your Data Lake with Amazon QuickSight Q
summary
Amazon QuickSight Q runs ML-powered natural language queries over uploaded datasets and AWS sources, demonstrated by building an Olympics topic from CSVs, adding semantic types and synonyms, and splitting datasets to avoid double counting. The topic applies default filters (e.g., exclude non‑applicable medals, default to Summer unless explicitly asked) and returns counts, charts, and player profiles instantly — fixing an initial medal count from 30 to the correct 28 after a filter. The UI shows topic creation steps, user activity and verified answers for QA.
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chapters (5)
- 0:00Introduction to QuickSight Q
- 3:55Demo of natural language queries
- 15:25Creating a Q topic from scratch
- 27:04Data modeling for QuickSight Q
- 38:10Closing and Q&A
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