SQL Data Analysis Practice

Overview

This repository contains practice exercises and solutions for SQL data analysis, based on a course I completed on LinkedIn Learning. The course covered various SQL concepts, including handling missing values, working with dates, common SQL functions, and data visualization.

Source

This is a forked repository, originally provided as part of the LinkedIn Learning course on SQL data analysis. The full course is available from LinkedIn Learning. The original repository contained datasets and exercise files, which have been used here for practice and further learning.

Course Highlights

• Data Cleaning: Techniques to identify and handle missing or inaccurate values.
• Date Functions: Working with dates for data analysis, including filtering and formatting.
• Common SQL Functions: Usage of aggregate functions, string functions, and conditional logic in SQL.
• Data Visualization: Basic data visualization techniques using SQL queries.

How to Use

1. Clone the Repository

   git clone https://github.com/yourusername/sql-data-analysis-practice.git

2. Navigate to the Project Directory

   cd sql-data-analysis-practice

3. Open the SQL Files
   • Use any SQL-compatible database system (e.g., MySQL, MSSQL, PostgreSQL) to run the scripts.
   • Load the datasets from the datasets folder and execute the SQL scripts from the exercises or solutions folder.

License

This repository is for educational purposes and follows the licensing terms of the original forked repository. Please refer to the LICENSE file for more details.

Acknowledgments

• LinkedIn Learning for providing the SQL Data Analysis course and the original repository.
• The course instructor for guiding through the various aspects of SQL data analysis.