Chatting with your Data: Conversational Analytics in BigQuery

📰 Dev.to · Aryan Irani

Learn how to use conversational analytics in BigQuery to simplify your data analysis workflow and get insights faster

intermediate Published 20 Jun 2026
Action Steps
  1. Set up a BigQuery project to store and manage your data
  2. Use the BigQuery console to create a conversational analytics interface
  3. Configure natural language processing (NLP) to interpret user queries
  4. Test and refine your conversational analytics workflow
  5. Apply conversational analytics to your existing data analysis tasks
Who Needs to Know This

Data analysts and business intelligence professionals can benefit from this approach to make data analysis more efficient and accessible

Key Insight

💡 Conversational analytics can make data analysis more accessible and efficient by allowing users to interact with data using natural language

Share This
💡 Simplify data analysis with conversational analytics in BigQuery! #BigQuery #ConversationalAnalytics

Key Takeaways

Learn how to use conversational analytics in BigQuery to simplify your data analysis workflow and get insights faster

Full Article

For the last decade, the workflow for Business Intelligence hasn't changed much: A business...
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