Warehouse setup
Creates raw and analytics schemas, stages payroll/budget inputs, and converts source files into typed analytical tables.
Skill evidence
This page connects the Postgres SQL skill directly to the public GitHub repository built from the BudgetDB analytics work: data extraction, cleanup, employee normalization, cost modeling, QA checks, and executive-ready views.
Published project
The repository shows how raw payroll, vendor, commission, T&E, and planning-style inputs become a reusable analytics layer for finance and people-operations reporting.
What this proves
Repository work map
Each block below links the skill back to SQL files in the public repository.
Creates raw and analytics schemas, stages payroll/budget inputs, and converts source files into typed analytical tables.
Builds a canonical employee layer with employee IDs, team, role, salary, benefits, employment windows, and normalized name keys.
Normalizes messy commission names, adds deterministic matching keys, and uses an override bridge for manual name-to-employee governance.
Generates month-level payroll, benefits, vendor, commission, and T&E cost facts that can feed dashboards and executive reviews.
Allocates software and vendor spend by employee and team using reusable views, headcount logic, and department ownership patterns.
Creates monthly burn, annual spend, vendor dashboard, annual cost per employee, and executive operations insight views.
Skill summary
The repo shows the full path from extracting source files to building trusted views: raw schemas, cleaned tables, employee matching, monthly facts, scenario foundations, allocation logic, and executive QA.