Product Analytics. Part 2 Calculating D1-D30 retention curve. Part 2

194. Calculating D1-D30 retention curve. Part 2

👉 In this exercise you need to calculate D14 retention rate for users who signed up on Feb 1, 2018.

⚠ The purpose of this exercise is to finish the retention curve query we started in the previous lesson. 📈 It gives us the number of active users per day. The challenge is to complete the query and calculate retention rate for each day.

⚠ Submit only the integer part of the retention rate as the answer. For example, if D14 retention rate is 17.666% submit 17 as the answer.

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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 mobile_analytics.events
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