What a Data Governance Maturity Assessment Actually Looks Like
You cannot improve what you have not measured. Here is what a typical assessment engagement looks like, the five dimensions we evaluate, and the common findings.
Coming Soon10 min read
Insights
Practical guidance on data governance, AI governance, software architecture, and the future of agentic AI development. Written by Joshua Garza.
AI Governance
The EU AI Act Compliance Deadline Is August 2, 2026. Here's What You Actually Need to Do.
A practical guide to the five most common compliance gaps and a step-by-step readiness checklist for organizations deploying high-risk AI systems.
Joshua GarzaComing Soon12 min read
Upcoming Posts
Dark Factory Principles: How Autonomous AI Agents Are Changing Software Delivery
From the dark factory concept in manufacturing to its application in software development. The five levels of AI-assisted development and what Level 5 looks like in practice.
Coming Soon15 min read
Your AI System Inventory Is Incomplete. Here's Why That's a Problem.
Most organizations cannot enumerate their AI systems in production. The EU AI Act requires a complete inventory. Here is what to capture and how to conduct one.
Coming Soon8 min read
Technical Debt Quantification: How to Make the Business Case for Architecture Modernization
Why "we have technical debt" is not a compelling argument to the C-suite, and a framework for presenting modernization as ROI, not cost.
Coming Soon11 min read
Data Quality Rules That Actually Work: Moving Beyond Row Counts and Null Checks
The problem with basic data quality checks and a tiered approach: schema validation, statistical profiling, business rule validation, and cross-dataset consistency.
Coming Soon9 min read
Topics We Cover
Data Governance
Maturity assessments, policy development, stewardship, data quality culture
AI Governance
EU AI Act, NIST AI RMF, AI system inventory, bias testing, compliance
Software Architecture
Technical debt, modernization, microservices, API design, cloud migration
Agentic AI
Dark factory principles, scenario-based validation, autonomous agents, Digital Twin environments
Data Quality
Data quality rules, observability, monitoring, SLAs, tools and frameworks
Leadership & Strategy
Fractional CTO, data strategy, technology leadership, team building
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