42. Analyzing feature: counting users who filled their profile

When a new feature gets released or modified it usually means that there are a bunch of tables or columns were added to the database. To measure the so-called feature acceptance we can calculate the percentage of the users who actually had a meaningful interaction with it.

A good acceptance criterion for public profiles on Bindle could be the percentage of users who actually filled them up. In this exercise let’s calculate just the total count of users who filled their interests.

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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.

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-- Type in your query here. You might want to start by listing all records: SELECT * FROM profiles
LIMIT 500
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