Fractional Data and AI Advisor
Cory Holmes
I help executive teams build the enterprise data strategy, business intelligence infrastructure, and governance model that turn data into decisions and lay the foundation for AI experiences that actually work.
Four disciplines. One integrated practice.
Organizations don't struggle to collect data. They struggle to turn it into reliable intelligence, governed access, and the clean foundation that AI experiences require. My practice is built around closing that gap, starting at the executive level.
01
Data Management
Designing the unified data platforms and pipeline architectures that make enterprise reporting reliable and consistent, consolidating fragmented BI tools into a single governed environment that scales with the organization.
02
Data Strategy
Partnering with executive leadership to define the data vision, align every platform decision to business outcomes, and ensure the organization's data investments improve member experience, drive growth, and support strategic decision making.
03
Data Governance
Building the data ownership models, access controls, security frameworks, and content endorsement systems that make enterprise reporting trustworthy, and self-service analytics scalable without losing control of what gets published.
04
AI-Ready Data
AI experiences are only as good as the data behind them. I help organizations build the data quality standards, governance model, and clean foundation that AI-powered analytics and features require, before the first model is trained.
Positions worth taking, because most organizations are getting these wrong.
Data Strategy
"Choosing the platform before you understand the requirements is the most expensive mistake in data."
Most organizations select Fabric, Databricks, or Snowflake, then spend months discovering what the platform can't deliver for their specific business context. Requirements first is not a best practice. It is the difference between a platform that serves the business and one the business works around.
Business Intelligence
"Two reports showing different numbers for the same metric is a governance failure, not a reporting problem."
When executives can't agree on which dashboard to trust, the issue isn't the visualization tool. It's the absence of a governed semantic model where key business metrics are defined once and applied everywhere. That's a data strategy conversation, not a Power BI conversation.
AI-Ready Data
"Your AI experience is only as good as the data it runs on. Most organizations aren't ready."
Organizations racing to deploy AI-powered features are building on data that was never designed to support them: inconsistent formats, ungoverned quality, no clear lineage. The organizations that will win with AI are the ones investing in data readiness now, before the models are trained.