This repository contains a dual-project data analysis portfolio submitted as part of the Data Analysis Capstone at Digital Skillhub Africa. It includes Excel-based analysis of Amazon product reviews and SQL Server-based business intelligence insights for Kultra Mega Stores.
# **CapStone-Submission**
# **Analysis Report: Amazon Product Review & KMS Inventory SQL Analysis**
This portfolio contains two business-focused data analysis projects using Excel and SQL Server. The projects demonstrate the application of core analytics skills for uncovering insights, solving real-world business problems, and recommending strategic actions.
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## 1. Background and Overview of the Analysis
**Purpose**
To extract actionable insights from eCommerce review data (Amazon) and retail sales operations (KMS) using different tools and techniques.
**Scope**
- Amazon data: Focused on customer reviews across product categories and regions
- KMS data: Sales, profit, and shipping data from 2009–2012 for Abuja division
**Key Questions**
- Which products/categories receive the highest customer satisfaction?
- How efficiently are shipping methods aligned with order priority?
- Who are the most/least valuable customers?
**Methodology**
- Amazon: Excel-based descriptive analysis (pivot tables, charts)
- KMS: SQL Server queries (aggregations, grouping, filtering)
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## 2. Data Structure Overview
| Project | Tools | Key Fields |
|--------|-------|------------|
| **Amazon** | Excel | Product Category, Rating, Region, Verified Purchase |
| **KMS** | SQL Server | Sales, Profit, Ship Mode, Order Priority, Customer Segment |
Data cleaning involved converting text to numeric formats (especially in SQL), filtering missing values, and normalizing field types.
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## 3. Executive Summary
- **Amazon Review Insights**: Verified purchases had higher ratings; Electronics and Books performed best.
- **KMS Inventory Insights**: Office Supplies led in sales; high-priority orders often used the wrong (slow) shipping methods.
- **Business Impact**: Both businesses have clear optimization opportunities in customer engagement and logistics alignment.
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## 4. Recommendations
- **Amazon**: Encourage verified reviews, improve packaging, focus on high-rated categories.
- …