Course Outline
Introduction to BI Modernization with WrenAI
- Limitations inherent in legacy BI systems.
- Core capabilities offered by WrenAI.
- Drivers for modernization and expected business outcomes.
Assessing Legacy BI Environments
- Conducting an inventory of existing dashboards and reports.
- Identifying high-value use cases for modernization.
- Performing a gap analysis between legacy BI and WrenAI.
Adoption Strategy
- Engaging stakeholders and ensuring alignment.
- Launching pilot projects to demonstrate proof of value.
- Developing a roadmap for adoption.
Migration Planning
- Strategies for dashboard migration.
- Aligning and transforming data models.
- Ensuring operational continuity during migration.
Conversational Analytics with WrenAI
- Generating SQL queries from natural language.
- Enabling interactive data exploration.
- Designing user-centric analytics experiences.
Embedded GenBI
- Integrating WrenAI dashboards into applications.
- Utilizing APIs to extend BI capabilities.
- Exploring use cases for internal tools and customer-facing applications.
Change Management for BI Modernization
- Communicating changes effectively across the organization.
- Training teams and facilitating upskilling.
- Measuring the success of adoption efforts.
Scaling and Future Evolution
- Expanding adoption across various business units.
- Establishing governance and standardization in modern BI.
- Anticipating future trends in conversational and generative BI.
Summary and Next Steps
Requirements
- A solid understanding of business intelligence workflows.
- Practical experience with legacy BI platforms and dashboards.
- Familiarity with organizational change management principles.
Target Audience
- BI managers.
- Data platform Product Managers (PMs).
- Solutions architects.
Testimonials (4)
Abhi has excellent knowledge of Alteryx and he explained things very clearly. He understood our goals and created bespoke demo datasets that were relevant to our organisation, which was very impressive. The training was well-structured and delivered at a good pace, with time for questions.
Samuel Taylor - Manchester Metropolitan University
Course - Alteryx for Data Analysis
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
Used good examples, good pace of the training and covered most things
