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Dec 22, 20249 min readML-Powered

QuickSight Q: Natural Language Queries

Discover how to let users ask questions in natural language and get instant visualizations.

What is QuickSight Q?

QuickSight Q is a machine learning-powered feature that allows business users to ask questions about their data using natural language. Instead of building visualizations manually, users can simply type questions like "What were our sales last quarter?" and get instant answers.

🧠 How Q Works

1

Natural Language Processing

Q uses NLP to understand the intent behind your question.

2

Semantic Mapping

Maps business terms to your actual data fields and tables.

3

Auto-Visualization

Automatically selects the best chart type for your answer.

Example Questions

"What were total sales last month?"
"Show me revenue by region"
"Top 10 products by profit"
"Compare Q1 vs Q2 performance"
"Which customers churned this year?"
"Forecast next quarter sales"

Setting Up Topics

Topics are the foundation of QuickSight Q. They define the data and business context that Q uses to answer questions.

Add Datasets

Connect the datasets that contain your business data. Q will analyze the schema automatically.

Define Synonyms

Add business-friendly synonyms for technical field names (e.g., "revenue" for "total_sales_amount").

Train & Validate

Review Q's understanding and provide feedback to improve accuracy over time.

🚀 Best Practices

  • Use descriptive field names that match business terminology
  • Add comprehensive synonyms for common terms
  • Regularly review and validate Q's answers
  • Create separate topics for different business domains