Welcome to this SQL learning repository! This space is designed to provide hands-on experience in SQL by working on diverse datasets and projects. Whether you're a beginner looking to grasp fundamental concepts or an advanced user aiming to refine your expertise, this repository offers practical exercises to deepen your understanding of SQL.
This repository contains various SQL projects, each targeting specific skills and concepts, ranging from data cleaning to advanced queries. By exploring these projects, you'll develop the ability to manage and manipulate data efficiently while learning best practices for structuring queries.
- Standardizing and converting data types.
- Handling missing or null values.
- Splitting and parsing complex string data into structured columns.
- Eliminating duplicates for data integrity.
- Dropping unused or redundant columns.
- Writing efficient SELECT statements.
- Applying conditions using WHERE clauses.
- Sorting and ordering results with ORDER BY.
- Creating and managing Common Table Expressions (CTEs) and temporary tables.
- Performing string manipulation using functions like
SUBSTRING,CHARINDEX, andPARSENAME. - Implementing conditional logic with CASE statements.
- Using aggregate functions such as SUM, MAX, and COUNT.
- Applying INNER and OUTER JOINs to combine datasets.
- Utilizing window functions to calculate rolling totals and rankings.
- Generating insights with grouped data using GROUP BY.
- Building views for reusable queries.
- Identifying key patterns and trends in datasets.
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Nashville Housing Data Cleaning
- Refined and transformed a real-world dataset by addressing null values, splitting address fields, standardizing dates, and removing duplicates.
- Learned string manipulation techniques, data deduplication, and column management.
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COVID-19 Data Exploration
- Analyzed COVID-19 trends globally and by country using aggregate functions and calculated fields.
- Gained insights into vaccination progress, case fatality rates, and infection percentages.
Clone this repository and start exploring the provided SQL scripts. Each project folder contains:
- A README file explaining the project's goals and steps.
- SQL scripts for executing queries.
- Notes on expected outcomes and learning objectives.
Feel free to modify the queries, experiment with new functions, or apply them to your datasets to broaden your SQL expertise.
Happy Learning! 🎉