Tableau Next agents can make analytics faster, more conversational, and easier to access, but what happens when the answer does not match the dashboard?
In this session, we’ll walk through a practical Tableau Next example where an agent returns the wrong number, why that mismatch happens, and how to fix it. We’ll cover how to anchor agent responses to a trusted source of truth, tune the semantic model, add business definitions, validate calculations, apply the right filters, and use verified questions to improve future responses.
Attendees will leave with a clearer understanding of how Tableau Next agents work, where mismatches can appear, and how data teams can build confidence before scaling agentic analytics across the business.
What attendees will learn
Why Tableau Next agents may return answers that differ from governed dashboards
How to use dashboards or gold tables as a source of truth
How semantic model tuning improves agent accuracy
Why field descriptions, filters, calculated fields, and business preferences matter
How verified questions help guide future agent responses
How to keep humans in the loop as agentic analytics scales
