Infrastructure Precedes Autonomy.
I build the governed data foundation, business intelligence and enterprise architecture that make data and AI investments perform.
The Iceberg Beneath Enterprise AI
Deploying autonomous AI models onto an ungoverned data estate is a capital drain. Without a governed foundation underneath, AI systems scan everything, trust nothing, and cost more every month.
Three liabilities show up before most organizations realize they have a foundation problem:
Runaway compute costs from unoptimized AI query loops that generate unpredictable cloud infrastructure invoices.
Contradictory metrics across business units because business logic was never defined in one place.
Brittle AI pipelines that break the moment a legacy schema shifts.
You cannot automate an estate you haven't engineered.
An Agent-Ready Data Estate is engineered below the waterline.
How I Work
I have built these foundations myself. Now I lead the work and own the outcome.
Relational Foundation Engineering
I fix the data foundation itself, so reporting and analytics stop contradicting each other and cost less to run.
Cloud Cost Ownership and Governance
I make cloud spend predictable by giving it an owner. Cost is the one major line item generated by engineering, paid by finance and accountable to nobody, and I close that gap without sacrificing performance.
Semantic Layer & Metrics Architecture
I establish the single source of truth between raw data and the tools that read it. Business definitions get locked in one place, so every report and every AI output means the same thing.
How I Engage: The Data Foundation Diagnostic
I don't begin with open-ended consulting agreements. Every engagement starts with a focused 30-day diagnostic designed to map your liabilities, quantify cloud waste, and benchmark your structural readiness for AI.
What you get at the end of 30 days:
Infrastructure Vulnerability Report: A line-by-line breakdown of hidden database inefficiencies and compute-heavy query risks.
Foundation Roadmap: An engineering-first blueprint detailing the exact relational changes required to make your data estate perform.
From there, we define the next step together based on what the diagnostic finds.
Dr. Malik Al-Amin
Data and Analytics Executive | Governance, BI and Data Architecture | Healthcare, Oil and Gas, Finance
I evaluate data problems through the lens of what the foundation can actually support, not the lens of whatever AI trend is current. More than twenty years as a database administrator, dimensional modeler, business intelligence developer and enterprise data director across healthcare, oil and gas and finance taught me where these problems actually live. My doctoral research confirmed it: executive sponsorship and governance as trust predict ROI more reliably than technology selection.