Course Outline
Overview of Business Intelligence Modernization via WrenAI
- Constraints associated with legacy business intelligence architectures
- Core functional capabilities of WrenAI
- Strategic drivers for modernization and expected operational outcomes
Evaluation of Existing Business Intelligence Environments
- Comprehensive inventory of current dashboards and reporting artifacts
- Identification of high-impact use cases
- Assessment of disparities between legacy systems and WrenAI functionality
Strategic Adoption Framework
- Stakeholder engagement and organizational alignment
- Implementation of pilot initiatives and validation of value
- Development of a structured adoption roadmap
Migration Planning Procedures
- Methodologies for dashboard migration
- Alignment and transformation of data models
- Maintenance of operational continuity during the transition period
Conversational Analytics via WrenAI
- Generation of SQL queries through natural language processing
- Interactive data exploration capabilities
- Design of user-centric analytics interfaces for government operations
Embedded Generative Business Intelligence
- Integration of WrenAI dashboards into existing application ecosystems
- Utilization of APIs to extend business intelligence functionality
- Application scenarios for internal tools and public-facing applications
Change Management for Business Intelligence Modernization
- Organization-wide communication of modernization efforts
- Training programs and workforce upskilling initiatives
- Metrics for evaluating adoption success
Scaling Initiatives and Future Evolution
- Expansion of adoption across multiple business units
- Governance frameworks and standardization in modern business intelligence
- Emerging trends in conversational and generative business intelligence technologies
Summary and Next Steps
Requirements
- A comprehensive grasp of business intelligence processes
- Prior involvement with established BI systems and reporting interfaces
- Knowledge of organizational change management frameworks
Intended Audience
- Business intelligence leadership
- Data platform project managers
- Solutions architects
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