Retail Sales Data Analysis & Reporting System

Analyzed 10,000 rows of raw retail sales
data and built a complete analytics system
with 11 professional charts and an automated
PDF report that runs with a single click.

The biggest challenge was identifying why
profit margins were inconsistent across
different product categories and regions
despite strong overall sales numbers.

Using Python and Pandas I cleaned and
transformed the raw data, removed errors
and inconsistencies and built a complete
analysis pipeline from scratch.

KEY FINDING:
Discounts above 40% were generating negative
profit across hundreds of transactions.
Capping discounts at 20% identified a
$50,000 annual profit recovery opportunity
the business did not know existed.

WHAT WAS DELIVERED:
1. Complete data cleaning and preparation
2. 11 professional charts covering sales
3. trends, profit margins, regional
4. performance and top products
5. Master dashboard image showing all
6. key metrics in one view Automated PDF report generator that
7. runs on any new sales data instantly
8 Business insights written in plain English

TOOLS USED:
Python, Pandas, Matplotlib, Seaborn,
FPDF, Microsoft Excel, SQL

PORTFOLIO:
github.com/gurleensainitamber15/
data-analytics-portfolio