👋 Welcome to my SQL World! Here, I showcase my expertise in SQL through exciting projects, along with the solutions to various interview questions that have further strengthened my skills. These experiences highlight my ability to analyze real-world datasets and extract actionable insights.
Objective: Analyze restaurant performance, customer preferences, and market trends.
- 🚀 Window Functions: Ranked restaurants by ratings within cities.
- 🔗 Joins: Merged location, cuisine, and rating data for deeper insights.
- 📊 Aggregations: Identified top cuisines and price ranges.
- 🛠️ Optimization: Improved query performance for large datasets.
Insights Delivered:
- 📍 Top-performing locations and cuisines.
- 💰 Ideal price ranges linked to customer satisfaction.
Objective: Explore user engagement and post performance trends.
- 🔄 Recursive Queries: Traced user interaction paths.
- 🧱 CTEs: Simplified complex time-series analysis.
- 🚀 Window Functions: Ranked posts by likes and comments.
- 🔗 Joins: Combined user activity, posts, and engagement data.
Insights Delivered:
- 🌟 Most engaging post types and peak activity times.
- 🔍 Patterns in user interaction and content sharing.
- 🔗 Basic to Advanced SQL : Including joins, aggregations, subqueries, and CTEs.
- 🚀 Window Functions : For ranking, aggregating, and analyzing data within partitions.
- 🔄 Recursive Queries : For hierarchical and path analysis.
- 🛠️ Performance Optimization: Writing efficient queries for large datasets.
I’m open to opportunities in Data Analytics, Data Science, or related fields.
- 📧 Email: [email protected]
💡 Thank you for visiting my portfolio!