AIData Systems & AI LabData Modeling · Statistical Reasoning · AI OrchestrationContact

Skill evidence

Postgres SQL work: finance and workforce analytics warehouse.

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

PostgreSQL Finance & Workforce Analytics Warehouse

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

CREATE SCHEMA, CREATE TABLE, CREATE VIEW, and CREATE OR REPLACE VIEW
COPY-based CSV ingestion with public-safe path placeholders
INSERT ... SELECT and ON CONFLICT DO UPDATE upsert logic
CTEs, LEFT JOINs, CROSS JOIN LATERAL, and generate_series month spines
REGEXP_REPLACE, REGEXP_SPLIT_TO_ARRAY, TRIM, LOWER, SPLIT_PART, and COALESCE
SUM, COUNT DISTINCT, FILTER, ROUND, CASE, and grouped reporting views
Bridge tables for manual match overrides and audit-friendly governance
Source-to-fact QA checks with variance and pass/review status

Repository work map

The GitHub project is organized around real analytics engineering tasks.

Each block below links the skill back to SQL files in the public repository.

Skill summary

Postgres SQL is the foundation skill behind the BudgetDB story.

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.