Dashboards and alarms Simple fraud detection

242. Simple fraud detection

This exercise is based on theLive dataset.

This exercise is a prequel to SQL alarms and outlier events detection.

This time we’ll look at detecting fraudulent payments. A good example is bad affiliate partnerships– a company agrees on a revenue share with a partner that promotes our product. Sometimes partners cheat and purchase our product themselves, then refund and hope that we won’t notice and pay them their “revenue share”.

👉 Your job today is to find a day in the past month with the highest percentage of refunded purchases.

⚠ Only consider dates that have at least 5 purchases...

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Anatoli Makarevich, author of SQL Habit About SQL Habit

Hi, it’s Anatoli, the author of SQL Habit. 👋

SQL Habit is a course (or, as some of the students say, “business simulator”). It’s based on a story of a fictional startup called Bindle. You’ll play a role of their Data Analyst 📊 and solve real-life challenges from Business, Marketing, and Product Management.

SQL Habit course is made of bite-sized lessons and exercises (you’re looking at one atm). They always have a real-life setting and detailed explanations. You can immediately apply everything you’ve learned at work. 🚀

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-- Type in your query here. You might want to start by listing all records: SELECT * FROM purchases
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