Financial Performance & Variance Analysis (PostgreSQL)

Overview

I built this project to demonstrate a finance-style reporting workflow using PostgreSQL and SQL. I loaded a retail transactions dataset into Postgres, engineered key financial fields (cost and budget), and then produced FP&A-style outputs such as gross margin trends and budget vs actual variance. This is meant to simulate how a business operations tream would analyze metrics such as revenue,margin, and budget variance using SQL.

Components

• A staging table (superstore_raw) to ingest the raw CSV
• A reporting table (transactions) with derived financial fields:
  • Cost = Sales - Profit
  • Budget Revenue = Sales × 1.05
  • Budget Cost = Cost × 1.03
• A set of SQL queries to generate decision-ready financial reporting outputs

Dataset

• Sample Superstore retail dataset
• ~9,994 rows of order-level transactions
• Fields used: Order Date, Sales, Profit, Category, Sub-Category, Region, Discount

Analyses (Outputs)

The SQL queries in /sql/03_financial_analysis.sql generate:

1. Monthly financials: revenue, cost, gross profit, gross margin %
2. Budget vs actual variance: revenue variance and cost variance by month
3. Variance by region: which regions are over/under budget
4. Profitability by category: margin % by category
5. Top cost drivers: sub-categories contributing most to total cost
6. Discount impact: profit margin by discount bucket

All query results are exported to /outputs as CSV files.

How to Reproduce

1. Create tables using: /sql/01_create_tables.sql
2. Load data into superstore_raw (CSV import)
3. Transform into transactions using: /sql/02_transform_insert.sql
4. Run analysis queries from: /sql/03_financial_analysis.sql

Skills Demonstrated

• SQL data ingestion + transformation
• Financial metric engineering (cost, margin)
• Budget vs actual variance analysis
• Aggregation, CASE logic, subqueries
• Business-focused reporting outputs