Project 2

Sharing My Experience: Exploring Alumni Career Paths with SQL

I've just completed an interesting SQL project for Skill Lync, where I explored the career choices of alumni from two universities. The project involved analyzing career trends based on higher studies, self-employment, and service/job records from six CSV datasets representing these categories for College A and College B.

Here's what I learned during this project:

1. Data Management with SQL: The project began by creating a new schema for alumni data and importing the CSV files into a MySQL database. This experience solidified my understanding of schema creation, table structure, and data import processes.

2. Data Cleaning and Preparation: I had to clean the data in each of the six datasets by removing null values, which is crucial for accurate analysis. This step involved creating views for cleaned data, demonstrating the importance of data preprocessing in SQL.

3. Custom SQL Procedures: I created procedures to convert records to lowercase, enhancing data consistency. This step showed me how string functions and stored procedures can improve data quality.

4. Data Visualization with Excel: Once the data was cleaned and organized, I imported the records into Excel to create pivot charts that visually represented the location of alumni. This task demonstrated how SQL data can be seamlessly integrated with Excel for visualization.

5. Cursor-Based SQL Procedures: The project included writing SQL queries to create cursor-based procedures for fetching names from College A and College B. This exercise highlighted the power of cursors in handling complex SQL queries.

6. Career Choice Analysis: Finally, I calculated the percentage of career choices among alumni from College A and College B, providing insights into their career trajectories. This step involved aggregating and analyzing data to draw meaningful conclusions.

Overall, this project allowed me to apply SQL in real-world scenarios, reinforcing my understanding of data management, cleaning, visualization, and complex SQL queries. I'm excited to share my experience and look forward to tackling more challenging SQL projects in the future.