From Chaos to insights
DATA AIGENCY
The Problem
Sound Familiar?
01 Your data lives in 5+ different places
and nobody can agree on a single source of truth.02 Analysts spend 80% of their time cleaning data instead of actually using it.03 You're paying for automations but not getting ROI
from your AI & cloud investment.
What I build
3 ways I
transform your data stack
Each engagement is scoped clearly upfront. You always know what you're getting and when.01 Data Lakehouse Architecture
Design and build a production-grade lakehouse in Azure Fabric or GCP. Semantic layer, governance, medallion architecture done properly from day one.02 Pipelines & Automation
Reliable ELT/ETL pipelines, modeled with dbt, orchestrated with BQ/Python, Airflow or Fabric.
Clean data in, trusted data out.03 AI & ML-Ready Data Layers
Feature stores, training datasets, and analytics-ready layers that your ML team can actually use.
My favorite part.
Simple 3 step program
How it works
01 Intake call - understand your stack & goals02 Architecture proposal - clear scope, timeline, cost03 Build & handover - you own everything, documented
