Course Outline
Fundamentals of Conversational Analytics
- Defining conversational analytics and its significance for product teams
- Core WrenAI capabilities and high-level architecture overview
- Common product team workflows facilitated by Wren AI
Data Source Connectivity and Access Management
- Overview of supported data sources and ingestion methods
- Managing data access, permissions, and cross-source joins
- Best practices for handling sample datasets and sandbox environments
Semantic Modeling and Metric Standardization
- Designing a metrics layer with canonical definitions
- Developing reusable metrics and dimensions for product analytics
- Implementing versioning and governance for the semantic model
Natural-Language to SQL Processes
- Understanding how WrenAI converts NL queries to SQL and implementing validation strategies
- Effective prompting patterns and fallback mechanisms for product inquiries
- Managing ambiguity, refining clarifying questions, and designing intent
Self-Service BI and Embedded Applications
- Designing conversational dashboards and templates tailored for product teams
- Integrating Wren AI into product workflows and internal tooling
- Assessing the adoption rate and impact of self-service analytics
Quality Assurance, Evaluation, and Guardrails
- Testing NL-to-SQL precision and developing validation suites
- Tracking drift, data quality indicators, and auditing queries
- Ensuring safety, controlling access, and enforcing business-rule guardrails
Practical Workshop: Creating a Product Insights Flow
- Hands-on lab: Modeling a product metric, generating conversational queries, and verifying outcomes
- Building a self-service dashboard with accompanying user guidance
- Presentations, peer feedback, and developing next-step action plans
Recap and Future Directions
Requirements
- A solid grasp of product metrics and KPIs
- Prior 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
