Founder and principal
Stephen McDaniel leads YakData. He has spent his career moving complicated data and software problems from an ambiguous business need to working systems, across product management, software development, data architecture, analytics, client delivery, development leadership, and production AI.
Selected operating background
Operator, not commentator
A consequential AI system crosses business value, data, architecture, software, evaluation, workflow, controls, economics, and operating ownership. That range lets YakData find cross-system problems early, connect the decisions, and keep the work moving instead of optimizing one component in isolation.
Product leadership at Brio, SAS, Yahoo, and Tableau included new products, established product lines, customer requirements, prioritization, tradeoffs, and responsibility for products generating substantial annual revenue.
Analytics leadership at Netflix and later work at Microsoft reinforced the same operating discipline YakData uses now: begin with the decision, establish the evidence, and work backward into data, analytics, and implementation.
Work has included Oracle consulting, regulated pharmaceutical data systems, data-warehouse capability at Opsware, worldwide data-ingestion architecture for U.S. Navy Cyber, server-side systems, scalability, security, and production data platforms.
For five years Stephen led a roughly 40-person SAS software organization spanning engineering, management, UX, testing, and documentation. The job was not to replace specialists. It was to keep the product, architecture, implementation, release, and customer result coherent.
Production evidence
Measured against an explicit production acceptance standard, not a model leaderboard.
The decision was not “which model is smartest?” It was “what performance does the system actually require, what failures matter, and what economics survive production?” That is the level at which YakData works.
What this changes in an engagement
Cross-functional experience changes what gets noticed early, what gets challenged, and which risks are treated as first-class production concerns.
When the output is wrong, YakData also examines context, semantics, retrieval, workflow, system boundaries, acceptance logic, and human control.
Security, latency, cost, integration, maintainability, review burden, and failure recovery are treated as design inputs, not cleanup work after the demo.
The business consequence, system evidence, engineering tradeoff, and release decision are kept in one chain so the recommendation can survive scrutiny.
Trusted to teach experienced professionals
Stephen has taught experienced professionals how to make difficult analytical reasoning legible across executive, technical, and operating audiences.
INFORMS · American Marketing Association · TDWI
Princeton University · Brown University · University of Chicago · University of Washington, Seattle · North Carolina State University
Built, simplified, published
The same operating pattern runs through the books and teaching: find the governing structure inside complex technical work, then make it usable and explainable.
Stephen looks at what the business needs and works back to the technology. This insight is invaluable for improving ROI and driving quick wins from the analytical investment.
John LodmellCFO, Nordstrom Credit Services
Why teams bring YakData in
You need someone who can get to the real problem quickly, connect the business and technical decisions, and drive the work to a defensible result your team can own.