2 of 21

AGENDA

Introduction

Insights

Project Overview

Real -World Application and Impact

Data Wrangling

Data Analysis and Visualisation

Conclusion

Challenges and Learning

TABLE OF CONTENT

3 of 21

The Global SuperStore Analysis

Global Superstore is a large multinational retail company that sells a wide range of products, including furniture, office supplies, and technology, to customers across different regions worldwide.

BUSINESS PROBLEM

The dataset contains valuable information, but without proper analysis, it’s difficult to identify key performance drivers and opportunities for growth.

OBJECTIVES

# Identify top and low-performing regions, products, and segments

# Measure the impact of discounts and shipping modes

# Detect seasonal trends in sales and profitability

Provide clear, actionable recommendations

4 of 21

TOP 6 GLOBAL SUPERSTORE BUSINESS QUESTIONS

Sales & Profit by Region and Country

Discount Impact

Profitability by Product Category

Shipping Mode Analysis

Which regions and countries generate the highest and lowest sales and profit?

What is the impact of discounts on profit margins?

What are the most and least profitable product categories and sub-categories?

Which shipping modes are most used, and do they affect delivery time or order volume?

Customer Segment Performance

Seasonal & Monthly Trends

How do different customer segments perform in terms of sales and profit?

Are there seasonal or monthly trends in order volume and profitability?

5 of 21

The Entity Relationship Model (ERM) was created to identify Key Entities, Attributes and their Relationship providing a clear view of the data structure for SQL Design and Analysis

The Global SuperStore ERM

6 of 21

SQL-to-Power BI connection for seamless analysis

Data Cleaning & Merging Process

7 of 21

After finalizing the Cleaning, the Entity Relationship Diagram (ERD) was developed to define the database schema and table structures. Primary Keys (PKs) and Foreign Keys (FKs) were assigned to ensure data integrity and establish relationships between tables.

The Global SuperStore ERD

8 of 21

Exploratory Data Analysis (EDA)

Business Question:

Which countries generate the highest sales and profit?

Mexico leads with 73bn sales and 16bn profit.
Brazil and Indonesia follow in sales but with lower profits.
The United States shows relatively lower sales but higher profit margins.
Some countries (e.g., Dominican Republic) have minimal profits despite notable sales.

Top 10 Total Sales & Profit by Country

9 of 21

Bottom 10 Total Sales & Profit by Country

Business Question:

Which countries generate the Lowest sales and profit?

Bottom 10 Countries: Honduras, Panama, and Argentina show significant negative profits despite sales

10 of 21

Corporate

Home Office

Consumer

Customer Satisfaction

Segment Performance Comparison – Profitability & Sales

$17.11bn

$9.29bn

$5.56bn

$2.35bn

$1.57bn

$0.66bn

4.52%

$4.01%

4.53

13.71%

$16.87%

11.91%

Segments

Total Sales

Total Profits

Avg.Discount%

Avg.Profit Margin%

How do different customer segments perform in terms of sales and profit?

Business Question:

Consumer drives the highest sales, but Customer Satisfaction leads in profit margin, while Home Office remains the weakest segment.

11 of 21

Standard Class takes the longest (5 days), while Same Day delivers nearly instantly (0.04 days), highlighting major speed differences across shipping modes

Business Question:

"How does the choice of shipping mode impact delivery time?"

Average Delivery Days by Shipping Mode

12 of 21

Monthly Sales (Bn) & Profit Margin % — with 3-Month Moving Average

13 of 21

Hypothesis Test

Impact of Discounts on Profit Margin

Statistical Test Results (α=0.05)

Compared profit margins for orders with vs without discounts.
Applied multiple statistical tests at α = 0.05 (Welch, Mann–Whitney, Mood’s median).

Most tests had p-value < 0.05 → reject H₀.

Strong evidence discounts reduce profit margins.

14 of 21

Effect Size Analysis: Discounts vs. No Discounts

75% CI confirms the drop is statistically significant and substantial.

Mean difference (with − no): -575.48%
95% CI (Welch): [-593.98%, -556.99%]
Hedges’ g: -0.531 (large negative)
Cliff’s delta: -0.590 (large negative

15 of 21

Key Business Insights

# Orders with discounts have a 575% lower profit margin compared to non-discounted orders.

# Statistical tests (at 5% significance level) confirm this difference is not due to chance.

# Large negative effect sizes (Hedges’ g: -0.531, Cliff’s delta: -0.590) indicate a strong negative impact of discounts on profitability.

# High regional variability in profitability — East & West at 100% margin, Africa & EMEA unprofitable

# Discounts significantly reduce profit margins (large negative effect confirmed by hypothesis test)

# Standard Class dominates order volume; long delivery delays in Second Class impact efficiency

Recommendations

# Reassess discount strategy to focus only on strategic or seasonal promotions.

# Use targeted discounts for high-value or low-risk products to maintain profit margins

# Monitor post-discount sales vs. profit to evaluate promotion effectiveness

1 of 21

2 of 21

3 of 21

4 of 21

5 of 21

6 of 21

7 of 21

8 of 21

9 of 21

10 of 21

11 of 21

12 of 21

13 of 21

14 of 21

15 of 21

16 of 21

17 of 21

18 of 21

19 of 21

20 of 21

21 of 21