- Welcome
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Course Overview
- Models
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Models Introduction 2 min
- Creating & Editing Models
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Creating a Basic Model 6 min
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Editing Column Properties 4 min
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Role Playing Dimensions 6 min
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Global and Local Joins 5 min
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Adding Formulas to Models 5 min
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Adding Parameters to Models 5 min
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Adding Filters to Models 3 min
- Optimizing Models for Spotter
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Introduction to Setting Up Models for Spotter 10 min
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Setting Up Models for Spotter 3 min
- Using Semantic Integrations to Create Models
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Snowflake Semantic Views Integration 5 min
- Review
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Review 10 min
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Knowledge Check 5 min
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Feedback
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Semantic Models
Learn how to create Models that build a governed semantic layer for your data, enabling AI agents and business users to gain trusted insights based on approved business definitions — without requiring an understanding of the underlying data structure.
Models in ThoughtSpot serve as the foundation of the AI semantic layer — a governed business logic layer that sits between your data and the AI systems your teams rely on every day. Rather than leaving AI agents to infer meaning from raw table structures and column names, Models capture the definitions, relationships, joins, formulas, filters, and security rules that reflect how your business actually works. This ensures that when AI agents or business users ask questions, the answers are grounded in approved metric definitions and consistent business logic — not probabilistic guesses.
The Model editor provides a visual, intuitive environment for building this semantic foundation. You can construct data models by dragging and dropping tables and columns, define joins between tables, and navigate table and column views alongside formulas, filters, parameters, and settings — all through a tabbed interface designed for clarity and speed.
This course introduces Models and covers how to create and use them in your environment — so your data team can build the semantic layer that makes AI-driven analytics reliable, governed, and trusted across your organization.