02 THE BACKBONE

Stop overwriting history. Unify your siloed systems.

I build scalable data infrastructures including cloud data warehouses and lakehouses using tools like Snowflake, Databricks, and SQL Server to act as your enterprise's unshakeable single source of truth.

Map Your Architecture
The Bottleneck

The Cost of Doing Nothing

01

You are losing historical context. Because operational databases overwrite records during updates, churn, vintage, and retention analysis become mathematically impossible.

02

Analytical queries are crashing your production systems. Running heavy executive reports directly on a live CRM causes timeout errors and severely damages user experience.

03

Your data exists in five different silos. Without a centralized warehouse, your teams are forced to export CSVs and manually VLOOKUP data, virtually guaranteeing costly human errors.

Cloud Warehouse Architecture

SILOED SOURCES
ERP
CRM
APIs
↓
THE SINGLE SOURCE OF TRUTH
CLOUD DATA WAREHOUSE

SNOWFLAKE · DATABRICKS · SQL SERVER

↓
ANALYTICS CONSUMPTION
DBT MODELS & POWER BI DASHBOARDS
02 THE ENGAGEMENT

Scope & Deliverables

Every engagement is scoped strictly to your operational reality. No bloat. No guesswork.

01

Relational Snapshot DB

  • 3-5 Weeks Delivery Timeline
  • Historical Data Reconstruction (Parsing Audit Trails)
  • SQL Server Environment Setup
  • SSIS / ODBC Integration Layer
  • Basic Schema Documentation
Ideal For

Organizations that need to urgently recover lost historical data and centralize operational silos into a controlled SQL environment.

Most Common Scope 02

Modern Data Stack Rollout

  • 6-10 Weeks Delivery Timeline
  • Snowflake or Databricks Architecture
  • Fivetran / Airbyte Ingestion Implementation
  • Storage-Compute Separation Optimization
  • Row-Level Security & Role Governance
Ideal For

Scaling enterprises that are crashing their operational databases and require a massive-scale, cloud-native storage solution.

Post-Deployment

Operations & Maintenance

Data systems decay without active maintenance. My O&M retainers keep your infrastructure secure, optimized, and evolving alongside your business.

01

Data quality & freshness monitoring

02

Cloud compute cost optimization

03

Infrastructure scaling & new sources

04

Security updates & user governance

Frequently Asked Questions

Should we choose Snowflake, Databricks, or SQL Server? +
It depends entirely on your scale and existing ecosystem. If you are deeply embedded in Microsoft, SQL Server (or Microsoft Fabric) is seamless. Snowflake is ideal for massive-scale relational warehousing with zero-maintenance compute, while Databricks is unparalleled if you plan to introduce heavy Machine Learning pipelines later. I audit your exact needs before recommending the platform.
Can you recover historical data that our old system overwrote? +
In many cases, yes. I build specialized SSIS or Python extraction pipelines that parse your legacy system's raw, flattened audit logs. By applying strict dimensional modeling logic, we can mathematically reconstruct the historical timeline and store it permanently in the new data warehouse.
Will setting up a cloud warehouse disrupt our current reporting? +
No. I build the new infrastructure in parallel. Your current reporting systems remain live and untouched until the new data warehouse is fully tested, populated, and certified by your leadership. Only then do we execute a controlled cutover.

What Happens Next?

Your historical data is secured and your silos are centralized. The next move is applying Kimball modeling and dbt logic to turn that raw data into a certified semantic layer.

Explore Semantic Modeling →