Your initial analysis before you to start to write t-sql is excellent, because sometimes we never reading well the statement, the besth teacher Nate, thank you so much for this.
Hey, i love your work i hope you continue making videos even the audience isnt a lot, the people who follow you really loves and understand the value of this info. I love all your series and hope you dont lose your interest in making videos. Thank you!!!?
Thanks for the kind words! I'm glad you're finding these videos valuable. I don't plan to stop any time soon and hope to churn out at least 1 coding question video a week (going to take a break this week tho =)). I also plan to jump into some python programming and build some tools I use when doing data science work at my job. Let me know if you have any other video recommendations. Happy to accommodate.
I had my first interview with Meta today, and while one of the questions you discussed came up total percentage, not an exact version, but similar), I did struggle through the process. However, I received the right input. Unfortunately, I didn’t land the role.
@@stratascratch it will be pretty good to share similar content on python as well. I find your approach very practical. Keep up the good work you are doing for many learners like me. Thanks again.
Nate, Why would you not include "confirmation" message type? It seems like those are exactly the ones we're interested in. Confirmation is the first step, the second step is for the user to confirm the confirmation. Calculate the percentage where the confirmation is confirmed. The other types of communication ("message" and "friend request") would be something like "you have a friend request" or "Janie posted on your wall" and should be filtered out.
I have the same situation as Adam at the beginning that made me go with the incorrect solution. The truth is the real confirmed messages are not those marked as ' confirmation' explicitly, and we need to link the tables and match the date and phone name to see which messages are the real confirmed messages.
There's so many assumptions that need to be aligned. If you don't get clarity about the assumptions, you could go down the wrong path. So definitely know what you mean. Thanks for your comment.
In the problem statement it said that friend_requests and invalid confirmation text messages were inserted in the table on accident so that's why I filtered them out.
I got confused with Invalid confirmation. I was thinking that there are mix of valid and invalid confirmation types. particularly this line -'Confirmation texts are only valid on the date they were sent.' (means message+valid confirmation(after join) will be valid) .This will give the result(11.14 %).I guess, I get confused(or overthink) with understanding the language of these question. How to avoid this trap! Mostly happens for many Facebook questions.
That’s the hardest part of interviews! My advice is to always ask the interviewer for clarity on how you’re interpreting the question. Don’t write any code until it’s totally clear to you.
![Tricky Data Science Interview Question [By Facebook]](http://i.ytimg.com/vi/eC7MdwKCCOE/mqdefault.jpg)
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Your initial analysis before you to start to write t-sql is excellent, because sometimes we never reading well the statement, the besth teacher Nate, thank you so much for this.
Hey, i love your work i hope you continue making videos even the audience isnt a lot, the people who follow you really loves and understand the value of this info. I love all your series and hope you dont lose your interest in making videos. Thank you!!!?
Thanks for the kind words! I'm glad you're finding these videos valuable. I don't plan to stop any time soon and hope to churn out at least 1 coding question video a week (going to take a break this week tho =)). I also plan to jump into some python programming and build some tools I use when doing data science work at my job. Let me know if you have any other video recommendations. Happy to accommodate.
Loved the initial break down of the problem before you started writing the query. Thanks.
That's definitely very important! I never start coding until I really understand everything.
I had my first interview with Meta today, and while one of the questions you discussed came up total percentage, not an exact version, but similar), I did struggle through the process. However, I received the right input. Unfortunately, I didn’t land the role.
Thank you so much! Great resource!
Would you please making some interview videos for potential data analysts?
Yup! Most of these questions can be applied for data analysts also! i'll point out some specific DA questions in the future.
@@stratascratch Thank you!
Hey great resource brother. Thanks
Let me know if you want to see other type of content! I do a lot of SQL but can do some python as well =)
@@stratascratch it will be pretty good to share similar content on python as well. I find your approach very practical. Keep up the good work you are doing for many learners like me. Thanks again.
I feel this questions is easy to code out, but hard to get your head around about the denominator and numerator...
Nate,
Why would you not include "confirmation" message type? It seems like those are exactly the ones we're interested in. Confirmation is the first step, the second step is for the user to confirm the confirmation. Calculate the percentage where the confirmation is confirmed.
The other types of communication ("message" and "friend request") would be something like "you have a friend request" or "Janie posted on your wall" and should be filtered out.
Check the problem description. There's dirty data. The other table contains the real confirmations.
I have the same situation as Adam at the beginning that made me go with the incorrect solution. The truth is the real confirmed messages are not those marked as ' confirmation' explicitly, and we need to link the tables and match the date and phone name to see which messages are the real confirmed messages.
Problem like this always needs a long time to understand the meaning. Even though it is not hard at all
There's so many assumptions that need to be aligned. If you don't get clarity about the assumptions, you could go down the wrong path. So definitely know what you mean. Thanks for your comment.
why did you filter out freind_request? shouldnt that be part of "total texts" sent on that day? Its a small thing but just curious.
In the problem statement it said that friend_requests and invalid confirmation text messages were inserted in the table on accident so that's why I filtered them out.
I got confused with Invalid confirmation. I was thinking that there are mix of valid and invalid confirmation types. particularly this line -'Confirmation texts are only valid on the date they were sent.' (means message+valid confirmation(after join) will be valid) .This will give the result(11.14 %).I guess, I get confused(or overthink) with understanding the language of these question. How to avoid this trap! Mostly happens for many Facebook questions.
That’s the hardest part of interviews! My advice is to always ask the interviewer for clarity on how you’re interpreting the question. Don’t write any code until it’s totally clear to you.