Course Outline
Introduction to Conversational Analytics
- Understanding conversational analytics and its significance for product teams.
- Overview of WrenAI’s core capabilities and high-level architecture.
- Common product team workflows facilitated by Wren AI.
Connecting Data Sources and Managing Access
- Supported data sources and typical ingestion patterns.
- Managing data access, permissions, and multi-source joins.
- Best practices for utilizing sample datasets and sandbox environments.
Semantic Modeling and Metrics Standardization
- Designing a metrics layer with canonical definitions.
- Developing reusable metrics and dimensions for product analytics.
- Versioning and governing the semantic model.
Natural-Language to SQL Workflows
- How WrenAI translates NL queries to SQL, along with validation strategies.
- Prompting patterns and fallback mechanisms for answering product questions.
- Managing ambiguity, clarifying questions, and designing for intent.
Self-Service BI and Embedded Applications
- Creating conversational dashboards and templates tailored for product teams.
- Integrating Wren AI into product workflows and internal tools.
- Evaluating the adoption rate and business 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 conducting query audits.
- Ensuring safety, access control, and implementing business-rule guardrails.
Workshop: Creating a Product Insights Flow
- Hands-on lab: Modeling a product metric, generating conversational queries, and verifying results.
- Building a self-service dashboard with user guidance.
- Presentations, peer feedback, and developing next-step action plans.
Summary and Future Directions
Requirements
- A solid grasp of product metrics and key performance indicators (KPIs).
- Prior experience utilizing data analysis or BI tools.
- Basic proficiency in 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