SQL Projects Portfolio

A collection of SQL projects demonstrating my skills in data exploration, relational queries, and business analysis. Topics include customer conversion, marketing attribution, subscription churn, revenue, and user engagement.

Projects

SQL Analysis Portfolio

Business analyses covering three areas:

• Funnel analysis: Track conversion from quiz participation to home try-on and purchase.
• Marketing attribution: Explore first-touch, last-touch, and purchase attribution by source and campaign.
• Churn analysis: Calculate monthly subscription churn overall and by customer segment.

Includes SQL queries and a churn analysis presentation.

SQL Business Metrics

Queries for measuring sales performance and player activity.

• Daily orders and revenue.
• Product revenue shares and reorder rates.
• Daily active users and average revenue per user.
• Next-day player retention.

SQL Multiple Tables Project

Four exercises focused on combining related tables:

• Lyft: Trips, riders, and autonomous vehicles.
• Reddit: Users, posts, and subreddit activity.
• VR Startup: Employee assignments and staffing needs.
• Welp: Business ratings and customer reviews.

Codecademy Learners Data

Explore learner profiles and course progress.

• Learner counts by email domain and location.
• Mobile app usage and hourly sign-up activity.
• Course progress across learner groups.

Twitch Data Analysis

Analyze viewing behavior and chat participation.

• Popular games and geographic viewing patterns.
• Video player usage and game genres.
• Hourly views in Brazil.
• Chat participation rates by game.

SQL Skills

• Data exploration: SELECT, DISTINCT, filtering, and sorting.
• Aggregations: COUNT, SUM, AVG, MIN, and MAX.
• Multiple tables: Inner, left, and cross joins, plus UNION.
• Query structure: Subqueries and common table expressions (CTEs).
• Conditional logic: CASE statements and null handling.
• Business metrics: Conversion, retention, churn, and revenue calculations.

Getting Started

1. Choose a project folder and read its overview.
2. Review the SQL queries and any included datasets.
3. Load the required data into a compatible SQL environment.
4. Run individual queries to explore the analysis.

Dataset availability varies by project. Several queries use SQLite syntax and may require adjustments for other database systems.

Purpose

Build practical SQL skills by turning business questions into queries and exploring patterns in customer, product, and activity data.