Data & Analytics

Analytics work depends on the data underneath a dashboard. I use SQL to examine sources and shape reporting datasets, Python to automate repeatable tasks, and explicit validation rules to make results dependable. Requirements and documentation connect technical choices back to business use.

Data quality and modernization

Legacy enterprise systems often contain decades of accumulated rules and inconsistent definitions. Work on modernization programs can include profiling, metadata, lineage, parsing, matching, transformation, business rules, validation, issue resolution and ongoing quality monitoring. The goal is to understand what a field means before changing how it is used.

Analytics automation

I build small tools when a manual process is repeated often enough to create delays or errors. A Python command-line utility I developed automated Tableau migration tasks including subscriptions, refresh schedules, custom-view exports and migration tagging. The tool provided a repeatable workflow for tasks that otherwise required substantial manual effort during Server-to-Cloud migrations.

Explore my operational reporting work and analytics automation project.