GENERATIVE BI CONSULTING
Move From Power BI to Generative BI With a Clear Plan
I help Power BI teams prepare their semantic models, business semantics, and data architecture for reliable conversational analytics with Microsoft Fabric.
Generative BI Requires More Than Adding Copilot
THE CHALLENGE
Organizations have spent years building Power BI models for dashboards, reports, and human analysts.
Generative BI changes the requirements.
When AI starts answering business questions directly, it has to understand far more than tables and columns. It needs clear definitions, trustworthy measures, business terminology, relationships, analytical rules, and context.
Models that work well for dashboards may still leave too much ambiguity for AI.
That is the gap I help Power BI teams close.
Power BI Teams Moving Toward AI
I don’t help every organization. I help organizations that:
Already have significant investment in Power BI
Are experimenting with Copilot or conversational analytics
Want more trustworthy AI answers from business data
Are evaluating Microsoft Fabric or Fabric IQ
Are unsure how semantic models and ontologies fit together
Want a practical roadmap rather than a wholesale rebuild
WHO THIS IS FOR
You Don’t Need to Start Over
Your existing Power BI semantic models already contain valuable business knowledge: measures, relationships, hierarchies, calculations, and years of modeling decisions.
The goal is not to replace that investment.
The goal is to make the meaning inside those models more explicit and usable by AI.
For many organizations, the most practical Generative BI journey starts by improving what they already have.
A PRACTICAL STARTING POINT
WHERE I HELP
Build the Semantic Foundation for Generative BI
Assess Your Current Environment
Understand how ready your existing Power BI semantic models are for AI and identify the areas most likely to affect accuracy, usability, and trust.
Strengthen Your Business Semantics
Improve the definitions, measures, terminology, relationships, analytical guidance, and business context AI depends on for reliable results.
Plan the Next Step
Develop a practical roadmap from enriched Power BI semantic models toward conversational analytics, Microsoft Fabric, Fabric IQ, and ontologies where appropriate.
What Generative BI Consulting Includes
Power BI semantic model AI-readiness assessments
Semantic model review and remediation
Business terminology and metric definition
AI instructions and analytical guidance
Model testing for conversational analytics
Semantic enrichment strategy
Fabric IQ and ontology readiness
Generative BI architecture and roadmap planning
ENGAGEMENT AREAS
Business Meaning Comes Before AI
My approach starts with the business meaning behind the data.
Before worrying about prompts, agents, or AI interfaces, I focus on whether the underlying semantic layer clearly communicates:
What the business concepts mean
How key metrics are calculated
How entities relate
Which assumptions matter
How common analytical questions should be interpreted
The more explicit that knowledge becomes, the less AI has to guess (the less it hallucinates).
MY APPROACH
RELATED EXPERTISE
Going Deeper
Power BI Models for AI
Learn how existing semantic models can be prepared for conversational analytics.
Semantic Model Enrichment
Explore the business semantics that AI needs to interpret your data correctly.
Fabric IQ & Ontologies
Understand where ontologies and Fabric IQ fit into the Generative BI journey.