SQL Data Analytics Project

Overview

This project demonstrates how SQL can be used to perform advanced data analytics on structured datasets to generate meaningful business insights.

The goal of this project is to simulate real-world analytical workflows by applying different analytical techniques commonly used in business intelligence and data analytics.

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Project Objectives

• Analyze business data using SQL queries
• Extract insights that support decision-making
• Apply different analytical patterns used in data analytics
• Build a structured analytics workflow

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Analytical Techniques Implemented

This project includes several key data analytics techniques:

Change Over Time Analysis

Analyzing trends and patterns in data over a period of time

Cumulative Analysis

Calculating running totals and cumulative metrics to measure growth.

Performance Analysis

Evaluating key performance indicators and comparing results across categories.

Part-to-Whole Analysis

Understanding the contribution of individual components relative to the whole.

Data Segmentation

Grouping data into meaningful segments for deeper analysis.

Reporting

Creating structured queries that generate business-ready reports.

Tools & Technologies

• SQL
• Relational Databases
• Data Analytics Techniques
• Business Intelligence Concepts

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👨‍💻 Author

Mohamed Ibrahim
Data Engineer

🚀 About Me

I am passionate about designing structured databases and transforming raw datasets into meaningful insights.
Recently completed the Associate Data Engineer in SQL track and currently building real-world SQL Server projects simulating business workflows.

I am actively seeking Data Engineering Internship opportunities.

📫 Connect With Me

📧 Email: mohamedibrahim45469@gmail.com
🔗 LinkedIn: https://www.linkedin.com/in/mohamed-ibrahim-b2aa1a32b