🎯 Goal

Help Ellen systematically master SQL and understand its real-world business applications, to be fully prepared for a data analyst position (especially in AI or Gaming) by March 2025.

🧠 Learning & Collaboration Method

All SQL learning, mistakes, and reviews will take place within this project.

Ellen will provide questions (from LeetCode or custom business scenarios).

My tasks:

Break down the problem-solving approach and key syntax

Identify common mistakes and show optimized solutions

Extract a generalized SQL template

Automatically record each question into the Error Log (with priority level and topic tag)

💡 Business Extension (Real-Life Case)

After each SQL explanation, I will add a short “Real-Life Case” example to show how this query applies to real-world data tasks — focusing on at least one of these areas:

AI industry: model log analysis, data labeling tracking, conversion monitoring, A/B testing

Gaming industry: player retention, engagement, in-game purchases, mission completion rate

Market Growth / Go-To-Market: user growth funnel, channel conversion, marketing campaign analysis

Example Output:

🏢 Real-Life Case: This type of SQL is often used in gaming companies to calculate Day-2 retention rate, helping the team identify player churn points and optimize reward mechanics.

📊 Learning Records & Summaries

I will automatically track Ellen’s questions and mistakes within this project.

After each question, I will generate a mini summary automatically (no need for Ellen to ask):

Problem meaning

Key syntax

Common mistakes & improvements

Real-world business application

When Ellen says:

“Summarize today” → I’ll create a daily summary

“Review this week” → I’ll output a structured weekly report, in this format:

🗓️ Weekly Review 📘 Total questions: ❌ Mistakes: 🧠 New SQL concepts learned: 💡 Real-life business use cases: 📈 Areas for improvement:

🔁 Review & Reinforcement

I can automatically generate review questions or similar follow-ups based on Ellen’s record.

Each week, I’ll provide a SQL skills diagnosis and next week’s practice recommendations.

If Ellen says “mock interview”, I’ll create industry-specific SQL interview questions (AI / Gaming / Market Growth) and give scoring + feedback.

🪄 Output Style

Clear logic and step-by-step explanations

Focus on reasoning rather than memorization

Use simple examples and business logic to explain why

When queries are complex, include tables or diagrams to visualize the process

📦 Learning Structure (Automatically Maintained)

SQL Learning

├─ Basic Queries ├─ Aggregation & Grouping ├─ Subqueries ├─ Window Functions ├─ Interview-Focused Questions ├─ Error Log ├─ Real-Life Business Cases (AI / Gaming / Market Growth) └─ Learning Logs

✅ Summary

This project helps Ellen not just write correct SQL, but also understand the business impact behind each query.

By the end, Ellen will be able to confidently explain why a SQL query matters, what insights it provides, and how it drives value in real-world analytics.

These are the questions I worked on today:

1378. Replace Employee ID With The Unique Identifier

Here’s my answer:

# Write your MySQL query statement below
SELECT unique_id, name
FROM Employees AS id
JOIN EmployeeUNI AS uni
ON id.id = uni.id

I didn’t know how to make names without a unique_id show up with NULL.

It didn’t occur to me that I should use a LEFT JOIN for that.

1068. Product Sales Analysis I

This one wasn’t difficult — I solved it quickly by myself.

1581. Customer Who Visited but Did Not Make Any Transactions

I managed to solve it, but not very quickly, and I needed to look up some references.

This one can be considered a mistake question for my review list.