SQL Data Analysis Portfolio Project

This project is based on the YouTube tutorial
🎥 SQL Data Analyst Portfolio Project | Like I Do in My Real Projects

It simulates a real-world SQL data analysis scenario, covering different types of analysis and reporting.

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📌 Objectives

The project demonstrates how to:

• Analyze data over time
• Perform cumulative and performance analysis
• Execute part-to-whole and segmentation analysis
• Generate actionable insights through SQL reports

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🔍 Analysis Types

• 📈 Changes Over Time
• 📊 Cumulative Analysis
• 🚀 Performance Analysis
• 🧩 Part-to-Whole Analysis
• 🔍 Data Segmentation

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📋 Final Deliverables

Two comprehensive reports saved as SQL views:

• Customer Report → 08_customer_report.sql
• Product Report → 09_report_customers_view.sql

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🛠️ SQL Techniques Used

• Basic SQL: SELECT, FROM, WHERE, GROUP BY, ORDER BY
• Intermediate: CASE WHEN, JOINS
• Advanced: Window Functions, CTEs, Subqueries

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📂 Files

scripts/ — SQL Analysis & Reporting Scripts

File	Description
00_init_database.sql	Initializes database schema and tables
01_changes_over_time_analysis_month.sql	Analyzes sales trends on a monthly basis
02_changes_over_time_analysis_year.sql	Analyzes sales trends on a yearly basis
03_cumulative_analysis.sql	Calculates cumulative metrics over time
04_performance_analysis.sql	Evaluates sales performance across dimensions
05_part_to_whole_analysis.sql	Analyzes sales contribution by segments
06_data_segmentation_cost.sql	Segments data based on cost-related criteria
07_data_segmentation_customer.sql	Segments data by customer characteristics
08_customer_report.sql	Constructs customer report logic
09_report_customers_view.sql	Creates a view for the customer report
10_product_report.sql	Constructs and saves the product report as a view

dataset/ — Source Data Tables

File	Description
gold.fact_sales.csv	Fact table containing transactional sales data
gold.report_customers.csv	Dimension table for customer information
gold.report_products.csv	Dimension table for product information

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💬 Feedback

If you have suggestions for improvements or feedback, feel free to connect on LinkedIn.

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📎 Credits

Inspired by the tutorial: SQL Data Analyst Portfolio Project | Like I Do in My Real Projects