FAQ: Why Data Science? - Exploring Data with SQL - Continued

Why does this return the churn rate to 100% instead of 25% as the original code? I replaced the second COUNT loop with COUNT(“march_cancellations”).

I can’t see the result after I run it took more than an hour what shall I do?

This may be a silly comment, but I don’t quite get the learning element here. I’m reading through the exercises and hitting run only to be shown code… Sounds silly but this is the second exercise in and I’ve learnt nothing apart from a few technical terms. Also, the concept reviews don’t exist. Am I missing something here?!

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This course does not teaching me SQL from the beginning do, i have to take another course to learn SQL from begining.

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In the context of calculating churn rate, what is the difference between voluntary and involuntary churn, and how can they be distinguished in a data analysis? Can you provide an example of a company and a scenario where this distinction could be important in understanding customer behavior?

Soooo am I supposed to understand any of that?
Or is it just so we can see an example of what a query looks like?

I ask because I thought this Foundation Path was for complete newbs with no experience (ie. me) , and now I’m wondering if I’m supposed to have done some pre-foundation course first?

…Or a pre-pre-foundation course :laughing:

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Hello! Just started today. 3/11 asks “What recommendations would you make to Codecademy based on Catherine’s analysis?”.

As someone brand new, I can see the three columns with the churn rate %. Is there an actual answer to what a recommendation would be just going off those three columns? The hint only mentions the three columns. I just want to make sure I’m not hung up on that page thinking there is an actual answer to the question.

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@micro8824623555 I’m a complete n00b, zero SQL experience. But based on the three columns displayed after running the query, I would personally recommend, if it were April of 2017, to maybe do some advertising or run some promo codes, as their churn rate has grown substantially in a month’s time. I don’t know what other recommendations could be made from the information provided. Have you come up with anything since you posted this? Is the learning course explaining things a little better in the next sections?

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Thanks for the giving some input. I feel you may be correct. I honestly just bookmarked it in my notes and assumed it would be covered/answered later on and I think there was a later example that mentions something as simple as advertising/promo to boost some metric.

I just started the Intro to SQL section. I feel everything before this section was a brief overview and I feel will now start to get more detailed

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I just finished “Analyse with SQL” (skill path) a few days ago. And we covered churn rate but the way we calculated the churn rate there was (Cancellations within month x / Total subscribers we have on day 1 of month x).

The one shown here is just cancellation/total subscribers. Can someone tell me the difference?

I actually have a question regarding the definition of churn rate given in the example. The example reads that there are 1000 subscribers, 250 cancel, 200 sign up and as a result the churn rate is 20.8%. Shouldn’t it be 25%? I always understood churn to mean how many of your existing customers leave. The 200 additional ones are not part of the existing number because they are just joining. So shouldn’t churn rate be calculated as a percentage of cancellation of the existing customers rather than existing customers + new signups?