Uploaded October 2020 | Updated September 2026, 12 hours ago

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This SQL data science interview question was asked by Facebook. I’ll cover both the question and answer and give a detailed explanation of the approach. I walkthrough each step of my answer, assumptions, approach, and explain every line of code I write. This is literally how I would answer every data science interview question and prepare for every data science interview at FAANG companies and others.

Link to question: platform.stratascratch.com/coding/10291-sms-confirmations-from-users?python=&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link

The question has multiple steps including applying a LEFT JOIN to multiple database tables, using a NOT IN to filter out rows based on values you want to exclude in the final answer,, and using the SQL count() function to help calculate a percentage. This question covers concepts that are commonly found in data science interviews at Facebook and Google.

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This series is for both beginner and intermediate data scientists and analysts interested in learning how to solve common data science interview questions in SQL. These are real data science interview questions. For some background context and an intro about what this series is about: bit.ly/36kKbxG

👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link

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Timestamps:

Intro: (0:00)
Question: (0:14)
Exploring the Data: (0:57)
Writing Out The Approach: (2:32)
Coding The Solution: (5:14)

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About The Platform:

I'm using StrataScratch, a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and python), statistics, probability, product sense, and business cases.

I created this platform because I wanted to build a resource to specifically help prepare data scientists for their technical interviews and to generally improve their analytical skills. Over my career as a data scientist, I never was able to find a dedicated platform for data science interview prep. LeetCode and HackerRank were the closest but these platforms specifically serve the computer developer community so their questions focus more on algorithms that working with data.

So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.

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Contact:

If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
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