Course Outline
Introduction to Conversational Analytics
- Understanding conversational analytics and its value for product teams
- Key capabilities and high-level architecture of WrenAI
- Common product team workflows facilitated by Wren AI
Data Source Connection and Access Management
- Overview of supported data sources and ingestion patterns
- Managing data access, permissions, and multi-source joins
- Best practices for handling sample datasets and sandbox environments
Semantic Modeling and Metrics Standardization
- Designing a metrics layer with canonical definitions
- Creating reusable metrics and dimensions for product analytics
- Implementing versioning and governance for the semantic model
Natural-Language to SQL Workflows
- How WrenAI translates natural language queries into SQL, along with validation strategies
- Effective prompting patterns and fallback mechanisms for product questions
- Managing ambiguity, clarifying questions, and intent design
Self-Service BI and Embedded Applications
- Designing conversational dashboards and templates tailored for product teams
- Integrating Wren AI into product workflows and internal tools
- Tracking adoption rates and measuring the impact of self-service analytics
Quality Assurance, Evaluation, and Guardrails
- Testing NL-to-SQL accuracy and constructing validation suites
- Monitoring data drift, quality signals, and auditing queries
- Ensuring safety, access control, and business-rule guardrails
Workshop: Building a Product Insights Flow
- Hands-on lab: Modeling a product metric, generating conversational queries, and verifying results
- Assembling a self-service dashboard with user guidance
- Presenting work, gathering feedback, and defining next-step action plans
Conclusion and Next Steps
Requirements
- A solid grasp of product metrics and Key Performance Indicators (KPIs)
- Practical experience with data analysis or BI tools
- Basic knowledge of SQL is advantageous
Target Audience
- Product Managers
- Data Analysts
- Data Champions within business units
Testimonials (3)
Deepthi was super attuned to my needs, she could tell when to add layers of complexity and when to hold back and take a more structured approach. Deepthi truly worked at my pace and ensured I was able to use the new functions /tools myself by first showing then letting me recreate the items myself which really helped embed the training. I could not be happier with the results of this training and with the level of expertise of Deepthi!
Deepthi - Invest Northern Ireland
Course - IBM Cognos Analytics
he was well prepared - and he is very sympathetic
Oliver - Post CH AG
Course - Splunk Fundamentals
lots of pratical exercises
