SQL Instagram DB Clone
Published:
Timeline: July 2023
Focus: Practicing SQL fundamentals with a simulated Instagram dataset
Source: Inspired by “The Ultimate MySQL Bootcamp” by Colt Steele
To learn the basics of SQL, I followed the full CRUD path from creating tables, loading sample data, and exploring insights. The project produces an Instagram clone schema (ig_clone_schema.sql) and a dataset (instagram_clone_data.sql) populated with users, posts, hashtags, and likes.
Questions Answered
- Oldest users: find the five earliest account registrations.
- Ad timing: identify which day of the week attracts the most signups.
- Inactive users: highlight accounts that never posted a photo.
- Top photo: surface the single most-liked image and its owner.
- Posting cadence: calculate how often the average user posts.
- Popular topics: rank the five most-used hashtags.
- Potential bots: detect users who liked every post.
Deliverables
schema and data/ig_clone_schema.sql: table definitions for users, photos, comments, likes, and tags.schema and data/instagram_clone_data.sql: synthetic Instagram activity data.solutions.sql: questions and answers exploring user behavior and content patterns.