Course Outline
Overview of Conversational Analytics
- Definition of conversational analytics and its significance for governmental operations
- Core capabilities and architectural components of WrenAI
- Standard operational workflows supported by Wren AI
Integration of Data Sources and Access Control
- Supported data feeds and ingestion methodologies
- Data access protocols, permission management, and multi-source data integration
- Recommended practices for sample data sets and secure sandbox environments
Semantic Modeling and Metric Standardization
- Establishing a metrics layer with authoritative definitions
- Developing reusable metrics and dimensions for operational analysis
- Version control and governance of the semantic model
Natural Language to SQL Translation Processes
- Mechanisms for converting natural language queries into SQL and validation methods
- Query patterns and fallback strategies for addressing operational inquiries
- Addressing ambiguity, clarifying requirements, and defining intent structures
Self-Service Business Intelligence and Integrated Applications
- Development of conversational dashboards and templates for operational teams
- Incorporating Wren AI into existing workflows and internal systems
- Assessing the adoption and impact of self-service analytics capabilities
Data Quality, Evaluation, and Security Controls
- Testing accuracy of NL-to-SQL translations and establishing validation suites
- Monitoring data drift, quality indicators, and query audits
- Ensuring security, access control, and adherence to business rule guardrails
Practical Exercise: Developing an Insight Workflow
- Hands-on laboratory: defining an operational metric, generating conversational queries, and verifying results
- Configuring a self-service dashboard and user guidance resources
- Presentations, feedback sessions, and development of action plans
Conclusion and Future Implementation Steps
Requirements
- Proficiency in operational metrics and key performance indicators
- Experience with data analysis or business intelligence tools
- Foundational knowledge of SQL is advantageous
Target Audience
- Program 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