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sql-challenge

Employee Database Analysis

Project Overview

The Employee Database Analysis project focuses on creating and analyzing a relational database to manage employee information, salary data, departmental structures, and managerial relationships within an organization. The project is built using PostgreSQL, encompassing data modeling, data importation, and comprehensive SQL queries to generate valuable insights from the employee dataset.

Objectives

1.    Data Modeling:
•    Use QuickDB to create an Entity-Relationship Diagram (ERD) and develop tables for Employees, Salaries, Titles, Departments, Dept_Manager, and Dept_Emp to reflect the relationships and constraints inherent in the data.
•    Implement primary keys, foreign keys, and data types to ensure data integrity and facilitate efficient querying.
2.    Data Importation:
•    Import CSV files containing employee data, salary information, job titles, department details, and managerial relationships into the corresponding SQL tables.
3.    Data Analysis:
•    Execute a series of SQL queries to derive insights from the database, including:
•    Listing employees with their details and salaries.
•    Identifying employees hired in specific years.
•    Extracting managerial relationships and department details.
•    Filtering employees based on specific criteria.
•    Counting the frequency of last names to identify common surnames within the organization.

Tools and Technologies

•    Database Management System: PostgreSQL
•    Data Analysis Language: SQL
•    Modeling Tool: QuickDB for creating the Entity-Relationship Diagram.
•    Development Environment: pgAdmin for database management and query execution.

Getting Started

1.    Clone the Repository:
    git clone <repository-url>
    cd <repository-directory>
2.    Set Up the Database:
    •    Install PostgreSQL and pgAdmin.
    •    Create a new database in pgAdmin.
    •    Run the SQL scripts to create tables and import data.
3.    Run SQL Queries:
    •    Use pgAdmin’s query tool to execute the provided SQL queries to analyze the data.

Acknowledgments

This project utilized assistance from ChatGPT to help with SQL queries, data modeling, and troubleshooting throughout the development process.

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