WrenAI OSS Deep Dive: Semantic Modeling, Text to SQL, and Guardrails Training Course

Introduction to WrenAI OSS

• High-level overview of the WrenAI architecture.
• Identification of key OSS components and the surrounding ecosystem.
• Guided installation and initial setup procedures.

Semantic Modeling in Wren AI

• The process of defining semantic layers.
• Creating reusable metrics and dimensions.
• Best practices for maintaining consistency and long-term maintainability.

Text to SQL in Practice

• Techniques for mapping natural language to SQL queries.
• Strategies to improve the accuracy of generated SQL.
• Addressing common challenges and troubleshooting methods.

Prompt Tuning and Optimization

• Effective prompt engineering strategies.
• Fine-tuning models for enterprise-grade datasets.
• Achieving a balance between output accuracy and system performance.

Implementing Guardrails

• Measures to prevent unsafe or resource-intensive queries.
• Establishing validation and approval workflows.
• Considering governance and compliance requirements.

Integrating WrenAI into Data Workflows

• Embedding Wren AI into existing data pipelines.
• Linking with BI and visualisation tools.
• Managing multi-user and enterprise-scale deployments.

Advanced Use Cases and Extensions

• Developing custom plugins and API integrations.
• Extending WrenAI's functionality with additional ML models.
• Strategies for scaling to handle large datasets.

Summary and Next Steps