Course Outline
Overview of Conversational Analytics
- Understanding conversational analytics and its value to product teams
- WrenAI core capabilities and architectural overview
- Common product team workflows facilitated by Wren AI
Data Source Integration and Access
- Compatible data sources and ingestion methods
- Managing data access, permissions, and multi-source joins
- Best practices for sample datasets and sandbox environments
Semantic Modeling and Metric Standardization
- Designing the 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 Processes
- How WrenAI converts NL queries to SQL and recommended validation approaches
- Prompting strategies and fallback options for product questions
- Managing ambiguity, clarifying queries, and intent design
Self-Service BI and Embedded Scenarios
- Creating conversational dashboards and templates for product teams
- Integrating Wren AI into product workflows and internal tools
- Tracking adoption rates and the impact of self-service analytics
Quality Assurance, Evaluation, and Guardrails
- Testing NL-to-SQL accuracy and developing validation suites
- Monitoring drift, data quality indicators, and query audits
- Security, access controls, and business-rule guardrails
Workshop: Creating a Product Insight Flow
- Practical lab: Modeling a product metric, generating conversational queries, and verifying outcomes
- Compiling a self-service dashboard with user guidance
- Presentations, feedback sessions, and subsequent action plans
Recap and Future Actions
Requirements
- Familiarity with product metrics and KPIs
- Prior 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
