Course Outline
Introduction to Conversational Analytics
- Understanding conversational analytics and its significance for product teams
- Overview of WrenAI’s core capabilities and architectural framework
- Common product team workflows facilitated by Wren AI
Data Source Connection and Access Management
- Supported data sources and integration patterns
- Managing data access, permissions, and multi-source joins
- Best practices for handling sample datasets and creating sandbox environments
Semantic Modeling and Metrics Standardization
- Crafting a metrics layer with canonical definitions
- Developing reusable metrics and dimensions for product analytics
- Implementing version control and governance for the semantic model
Natural-Language to SQL Workflows
- Exploring how WrenAI converts NL queries to SQL, including validation strategies
- Applying prompting patterns and fallback mechanisms for product queries
- Managing ambiguity, clarifying questions, and intent design
Self-Service BI and Embedded Applications
- Creating conversational dashboards and templates tailored for product teams
- Integrating Wren AI into product workflows and internal tooling
- Tracking adoption rates and measuring the impact of self-service analytics
Quality Assurance, Evaluation, and Guardrails
- Testing NL-to-SQL accuracy and developing validation test suites
- Monitoring data drift, quality signals, and conducting query audits
- Implementing safety measures, access controls, and business-rule guardrails
Workshop: Creating a Product Insights Flow
- Hands-on lab: Modeling a product metric, generating conversational queries, and verifying outcomes
- Assembling a self-service dashboard with user guidance
- Presentations, peer feedback, and defining next-step action plans
Summary 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
