Course Outline
Introduction to Conversational Analytics
- Defining conversational analytics and its relevance to product teams
- Overview of WrenAI's core features and architectural design
- Common product team workflows facilitated by Wren AI
Data Source Integration and Access Management
- Supported data sources and data ingestion methodologies
- Managing data access, permissions, and cross-source joins
- Best practices for handling sample datasets and sandbox environments
Semantic Modeling and Metrics Uniformity
- Architecting the metrics layer and establishing standard definitions
- Developing reusable metrics and dimensions for product analytics
- Implementing version control and governance for the semantic model
Natural-Language to SQL Processes
- Understanding WrenAI's NL-to-SQL translation and verification approaches
- Effective prompting techniques and fallback strategies for product queries
- Managing ambiguity, clarifying queries, and intent structuring
Self-Service BI and Embedded Applications
- Designing conversational dashboards and templates tailored for product teams
- Integrating Wren AI into product workflows and internal platforms
- Assessing the adoption rate and impact of self-service analytics
Quality Assurance, Evaluation, and Safety Measures
- Verifying NL-to-SQL accuracy and developing validation frameworks
- Tracking drift, data quality indicators, and audit query logs
- Enforcing safety protocols, access restrictions, and business rule guardrails
Workshop: Creating a Product Insights Pipeline
- Practical exercise: Modeling a product metric, generating conversational queries, and verifying outcomes
- Compiling a self-service dashboard with accompanying user instructions
- Presenting findings, gathering feedback, and defining action plans for future steps
Recap and Future Directions
Requirements
- Familiarity with product metrics and KPIs
- Prior experience with data analysis or BI tools
- Foundational knowledge of SQL is advantageous
Intended Audience
- Product managers
- Data analysts
- Data champions within business units
Testimonials (4)
Refactoring Exercise and Graph Visualization
Tiago Kocevar - Lang Energie AG / Osterwalder Zurich AG
Course - Business Intelligence and Data Analysis with Metabase
Machine Translated
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
