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SQL Toolkit - Advanced SQL and PL/SQL Examples

Introduction

Welcome to the SQL Toolkit repository, where I showcase my proficiency in Advanced SQL and PL/SQL coding. As a data-driven Business Analyst, I recognize the power of SQL queries and the advanced analytical capabilities that Recursive Queries and PL/pgSQL offer. In this repository, you will find three notable examples:

Examples

Fibonacci-by-RECURSIVE SQL

A recursive query can be a potent tool, but it has limitations, particularly in terms of self-referencing. To overcome this limitation, I've implemented a non-linear recursive query to calculate the Fibonacci series. This example demonstrates how you can employ recursive SQL to call a query inside itself as many times as needed, showcasing the versatility of SQL for complex calculations.

K_means

The K-means clustering method is a valuable technique for data analysis and segmentation. In this repository, you'll find an implementation of K-means clustering in SQL. This SQL algorithm can efficiently cluster large datasets, providing insights and patterns within your data. This is particularly useful for projects involving data segmentation and classification efficiently within the database.

Recursive Text Processing based on Finite State Machine (FSM)

PostgreSQL's regular expression library is a powerful tool for data cleaning and processing. However, there are scenarios where fine-grained control over the text-processing process is required. In this example, I demonstrate how to define a text-processing function in SQL without relying on PostgreSQL's regex. This approach allows us to have precise control over the data-processing pipeline, making it valuable for tasks such as data cleansing, text mining, and sentiment analysis—common tasks for data analysts.

Getting Started

To explore these advanced SQL and PL/SQL examples:

  1. Clone the repository to your local machine.

  2. Open the SQL scripts in your preferred SQL editor or IDE.

  3. Run the scripts to see the advanced SQL and PL/SQL code in action.

Feel free to explore the SQL scripts in this repository to learn, adapt, or use them in your own projects. If you have any questions, suggestions, or contributions, please don't hesitate to reach out.

Happy coding!

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