SQL Database Analytics Portfolio

This repository showcases SQL-based database analytics projects focused on relational database querying, table creation, data manipulation, joins, aggregation, filtering, subqueries, and structured data analysis. The projects demonstrate practical SQL skills used to retrieve, organize, transform, and analyze data stored in relational databases.

Repository Overview

The work in this repository focuses on using SQL to interact with structured datasets and relational database systems. The projects demonstrate how to write queries that extract meaningful information, combine data across tables, summarize records, and support data-driven decision-making.

Skills Demonstrated

• SQL programming
• Relational database querying
• Table creation and database structure
• Data filtering and sorting
• Inner joins and outer joins
• Multi-table queries
• Aggregation with COUNT, SUM, AVG, MIN, and MAX
• GROUP BY and HAVING clauses
• Subqueries
• Data manipulation
• Data cleaning using SQL logic
• Conditional logic with CASE
• Query organization and readability
• Structured data analysis

Technical Focus

Relational Database Querying

These projects demonstrate the use of SQL to retrieve and analyze data from relational databases. Queries are structured to answer analytical questions using filtering, sorting, grouping, and joins.

Joins and Multi-Table Analysis

The repository includes SQL workflows that combine data across multiple tables. This demonstrates the ability to work with relational data structures and connect related records using primary and foreign key logic.

Aggregation and Summary Analysis

The projects apply SQL aggregation functions to summarize data, calculate totals and averages, count records, and compare groups across categories.

Subqueries and Conditional Logic

The SQL scripts demonstrate more advanced querying techniques, including subqueries and conditional logic, to create flexible and meaningful analytical outputs.

Database Design and Data Manipulation

The repository includes SQL work related to creating, organizing, and modifying database tables. This reflects foundational skills in database structure and data management.

Tools and Technologies

• SQL
• Relational databases
• Database management systems
• Structured Query Language
• Data analysis
• Query development

Purpose

The purpose of this repository is to showcase practical SQL and relational database skills. It highlights the ability to write organized SQL queries, analyze structured data, join multiple tables, summarize results, and support database-driven analysis.

Author

Gilbert Morgan

Data Science Graduate Student
SQL | Database Analytics | Relational Databases | Data Analysis