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Course Outline

Introduction to Modernizing BI with WrenAI

  • Constraints and limitations of traditional BI systems
  • Defining the core capabilities of WrenAI
  • Business drivers and expected outcomes of modernization

Evaluating Current BI Environments

  • Cataloging existing dashboards and reports
  • Pinpointing high-value use cases for migration
  • Conducting gap analysis between legacy systems and WrenAI

Developing an Adoption Strategy

  • Securing stakeholder engagement and alignment
  • Executing pilot projects to demonstrate value
  • Constructing a comprehensive adoption roadmap

Planning the Migration

  • Effective strategies for dashboard migration
  • Aligning and transforming data models
  • Maintaining operational continuity during the transition

Leveraging Conversational Analytics with WrenAI

  • Generating SQL queries from natural language inputs
  • Facilitating interactive data exploration
  • Crafting user-centric analytics experiences

Implementing Embedded GenBI

  • Integrating WrenAI dashboards into application stacks
  • Utilizing APIs to extend BI functionality
  • Applying solutions for internal tools and customer-facing applications

Change Management for BI Modernization

  • Communicating the vision of change across the organization
  • Upskilling and training teams for new tools
  • Tracking and measuring adoption success

Scaling and Future Roadmaps

  • Expanding adoption across multiple business units
  • Establishing governance and standards in modern BI
  • Exploring emerging trends in conversational and generative BI

Conclusion and Next Steps

Requirements

  • Solid understanding of business intelligence workflows.
  • Practical experience working with legacy BI platforms and dashboards.
  • Knowledge of organizational change management frameworks.

Audience

  • BI Managers
  • Data Platform Product Managers
  • Solutions Architects
 14 Hours

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