Course Outline
Introduction to Conversational Analytics
- Defining conversational analytics and its significance for product teams
- Key capabilities of WrenAI and an overview of its architecture
- Common product team workflows supported by Wren AI
Connecting Data Sources and Access Control
- Supported data sources and data ingestion patterns
- Data access management, permissions, and multi-source joins
- Best practices for utilizing sample datasets and sandbox environments
Semantic Modeling and Metrics Standardization
- Constructing a metrics layer with canonical definitions
- Developing reusable metrics and dimensions for product analytics
- Version control and governance of the semantic model
Natural-Language to SQL Workflows
- How WrenAI converts NL queries into SQL and strategies for validation
- Prompting techniques and fallback mechanisms for product questions
- Managing ambiguity, clarifying queries, and designing intent
Self-Service BI and Embedded Use Cases
- Designing conversational dashboards and templates for product teams
- Integrating Wren AI into product workflows and internal tools
- Assessing the adoption rate and impact of self-service analytics
Quality, Evaluation, and Guardrails
- Testing the accuracy of NL-to-SQL and building validation suites
- Monitoring drift, data quality indicators, and query audits
- Ensuring safety, access control, and business-rule guardrails
Workshop: Build a Product Insights Flow
- Hands-on lab: model a product metric, generate conversational queries, and verify outcomes
- Assemble a self-service dashboard with user guidance
- Presentations, feedback sessions, and developing next-step action plans
Summary and Next Steps
Requirements
- A solid grasp of product metrics and KPIs
- Practical experience with data analysis or BI tools
- Fundamental 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
