Data Automation & Integration

Slash data-prep time by 80% with Power Query, Python & automated pipelines for B2B firms.

Turn Messy Data Into a Clean Central Repository

Problem

Analysts spend 60–80% of time prepping data; errors slip into reports.

Solution

I create ETL workflows using Power Query for Microsoft stacks and Python/Pandas for other sources. Data is deduped, validated, and landed in a single model table automatically.

Deliverables

My Four-Step Process

Audit & Mapping

Pipeline Design

Development & Testing

Handover & Documentation

80% reduction in manual prep time

Fewer “broken-link” errors

Scalable foundation for all analytics

Schedule a Data Automation Audit Schedule Now