Wade McNair
Enterprise data strategist and architect — data to AI leader
wademcnair
Knoxville, Tennessee
1.5K connections
Joined November 2025
Summary
Experienced enterprise data architect and strategist: across media companies and a national laboratory, Wade has led enterprise data architecture, stewardship, and governance programs—translating complex data needs into scalable architectures and programs that enable analytics and business outcomes. google+2
Research-driven practitioner with ORNL publications: Wade co-authored peer-reviewed work on text analysis, knowledge sharing, and readiness models for big-data investments while at Oak Ridge National Laboratory—showing a blend of applied research and production-focused IT leadership. ieee+1
Data strategy & GenAI advisor and public thinker: through Allen+Cass Consulting, Wade publishes practical guidance about GenAI readiness and the foundational importance of data management—positioning himself as a consultant who emphasizes people, process and data fundamentals before model adoption. allen-cass+1
Hybrid background spanning government labs, large media firms, and consulting: Wade’s career path (ORNL/UT-Battelle, Scripps, Discovery, EmployBridge, and consulting) indicates strengths in adapting enterprise data practices across regulated, research, and commercial environments. ornl+1
Work
Education
Projects
Writing
A Qualitative Readiness-Requirements Assessment Model for Enterprise Big Data Infrastructure Investment
January 1, 2014Paper on assessing readiness and requirements for enterprise big-data infrastructure investments (contributions to SPIE / Next-Generation Analyst proceedings).
A Text Analysis Approach to Motivate Knowledge Sharing via Microsoft SharePoint
January 1, 2012Conference paper describing a prototype using text analysis and machine learning to motivate and reduce overhead for knowledge sharing in enterprise SharePoint; pilot tested at Oak Ridge National Laboratory.
Concept of Operations for Knowledge Discovery from Big Data Across Enterprise Data Warehouses
2012-2014Work addressing operational concepts for knowledge discovery in large enterprise data warehouses (ORNL technical work).