This is very useful. Thanks a lot for sharing. I’m struggling now with my own case study for a portfolio. And it’s like when you understand everything, but don’t know what to start with 😅
Interesting case study and thanks for sharing your work with us. I see though that the middle part of this analysis is missing, the part which you manipulate the data and prepare it for analysis. You shared with us the first part, pretty interesting to see the raw process of thinking and identifying where should you look for insights and which questions should you try to answer. Then there is a gap and finally we are seeing the fruits of your analysis with charts, comments etc. Its equally important and crucial for all us data analysts to learn the tools you used, the process you followed, the data manipulation you did, like formulas, custom columns, pivot tables, maybe grouping any make more. That's real gold. What ever you can share, even in comments, would be highly highly appreciated and helpful for your audience🙂.
How did you work with the date-time format? I can see 01 03:08:09. That definitely signifies dd hh:mm:ss. Wouldn't you have a negative value or error if the time stamp falls in a new month? Like, having the order time at 31 23: 50: 59 and delivery time at 1 00 : 20: 45.
My way is using mid function to separate Day/HH/MM/SS and convert to the same unit (min or sec), with a if statement to check if delivered date and placed order date are not the same day and placed order date is 31, then to add give special calculation to those cases.
For a beginner that want to penetrate/transition to Data Analytics what books or subjects should I focus on? I do have basic excel knowledge and that's just about it. Thanks!
Hey there Mark! I'd recommend learning about the basics of statistics as that is core to data analysis and machine learning. There are plenty of books out there, or even video series (Skillshare, Coursera, TH-cam) where you can get started on this. Data becomes more fun when you seek out a dataset that is interesting to you! What I mean is: if you can ask basic data questions around a subject/topic you enjoy, you're more prone to seek out answers for something you already have interest in. Start with Stats, move on to SQL, and then Python. My recommendation is to look at a job you'd want to have in 1-2 years, and see what skills would be necessary to land that job!
Thanks for sharing. I have the same dataset for the interview and am getting the same numbers as you are showing in this video. Is it okay to follow your approach and present to them? I am sure they also know that the solution is already online for this. Wondering what's the catch here 😲
I think its best to take what you learn in this video and try to apply your own approaches. I am sure creative is valued, this intent is to be a starting point :)
Hello, these can be different for example. Customer placed order time is when customer placed the order while restaurant order placed time is when the restaurant time of order actually goes through. It depends on how the dataset is good to check if they are different or same.
Hey Mashiro! thanks for your question - we are trying something new and started a community page on Luma, let me know if you are interested to join and can ask questions there.
Thanks again for this AWESOME video! I have my assessment now and not the greatest with charts and graphs. Can anyone simply tell me how to manipulate the day and time fields to make pivot charts and graphs in excel ? I’m really struggling here.
@@simplya1651 Hey there! we are trying something new and started a community page on Luma, let me know if you are interested to join and can ask questions there.
I really doubt you passed this case. If restaurant 9 has such a high amount of daily average then how can restaurant 350 have higher average orders. it should be 9 or 20 or any other that generated higher revenue. if I take 30$ to be average order size then restaurant 350 does not even come close. The basic math is not sound
@@rontep6162 i actually got this case, merchant 9 has higher order volume and avg order amount as well. I also found the RFM of customers and clustered them and saw which region was better customer wise. I tried a few other things but did a lot of things similar to what is done in the video. But I was not taken to the next round. Very confused about this lol
Hi, for some reason when I comment on my laptop the comment is deleted. I just wanted to say it was an excellent video and I thought for the benefit of beginners or BI developers like myself wanting to transition to analytics, it would be great if you could do a follow-on video covering the many statistical concepts you implicitly relied on in this video. A question i had was on the last visualisation, have you split the data into quartiles ordered by delivery time (overall I assume ie placed to delivered), chosen the top 3 quartiles, and given the medians within those quartiles? And if yes, why did you choose to only show the top 3 rather than 4 quartiles and why did you find it of value to highlight in bold the second quartile (50%)? Thank you.
Do you mind sharing the link to your Facebook group, please? I am working on a similar exercise for big tech and would love to hear some feedback/insights.
This is super helpful for an analyst with a case study interview coming up, thank you!!
This is very useful. Thanks a lot for sharing. I’m struggling now with my own case study for a portfolio. And it’s like when you understand everything, but don’t know what to start with 😅
Interesting case study and thanks for sharing your work with us. I see though that the middle part of this analysis is missing, the part which you manipulate the data and prepare it for analysis. You shared with us the first part, pretty interesting to see the raw process of thinking and identifying where should you look for insights and which questions should you try to answer. Then there is a gap and finally we are seeing the fruits of your analysis with charts, comments etc. Its equally important and crucial for all us data analysts to learn the tools you used, the process you followed, the data manipulation you did, like formulas, custom columns, pivot tables, maybe grouping any make more. That's real gold. What ever you can share, even in comments, would be highly highly appreciated and helpful for your audience🙂.
True, next case study ill share more on the data manipulation piece. Thank you
Super useful! can you provide similar dataset?
Great video guy
Awesome example, thank you for sharing!
Hi thank you so much, where can i download this data set?
very insightful. Thanks.
Great video! You seemed bit nervous but is wonderful how you manage to teach us all this valuable info. Thanks!!
Thanks for deconstructing such type of case studies it was really useful.
Glad u found it useful Yash!
Hi, thanks for sharing! How can I find more Data Analytics Interview Cases for practice?
thanks for making this! You're helping a newbie!
Glad you enjoyed the video, we will make more videos. stay tune.
Thank you very much for sharing your results, I was given a similar case study and this was extremely helpful in perspectives and ideas, cheers!
Glad it was insightful
Hey Matt, could you please share the dataset, on like google docs if you would be kind sir!
Great content! thanks. Are you able to share how you created those charts? Thanks.
the graphs were created in google sheets
Hi This is really useful, where can I get this data set, thank you!
hey r u making this assignment for marketing analytics needed one help
This was such a great and helpful video. Thank you.
Great, if you enjoyed it please give it a like and subscribe for more content.
GREAT VIDEO! Thank you so much for sharing
Looking for a case study and got a technical test type :(
How did you work with the date-time format? I can see 01 03:08:09. That definitely signifies dd hh:mm:ss. Wouldn't you have a negative value or error if the time stamp falls in a new month? Like, having the order time at 31 23: 50: 59 and delivery time at 1 00 : 20: 45.
Bump on this. How was this and the timezone change to from UTC to PT calculated?
My way is using mid function to separate Day/HH/MM/SS and convert to the same unit (min or sec), with a if statement to check if delivered date and placed order date are not the same day and placed order date is 31, then to add give special calculation to those cases.
@@ching-yenlin855 Curious what kind of equation you applied to those cases where deliveries were the next day?
I’m not sure what to generalize from your presentation. It’s specific to those locations. Is there an overarching point?
Thank you for the video, I would like to know how to obtain a dataset like this?
hey r u making this assignment for marketing analytics needed one help
Can you please share the data set?
Thanks! Do you use more techniques ?
Thanks Noe, are you asking what additional techniques are useful for case studies?
@@learnanalyticsorg yep and another tools like python, thanks!
Where do one get link to that google doc you are sharing on the screen?
Hello is it possible for you to share the data sheet for one to practice with
great work, can you share the dataset?
Thanks for sharing.
Would the analysis have been possible with excel formulas - without using python/sql?
Yes of course, you can do both data analysis and data visualizations in excel. it is a powerful tool
Pls provide dataset and link for the same
For anyone looking for similar dataset, refer to this person's github, it is very similar. ghayward.github.io/TipsAnalysis_June2018.html
can you share masked data set or link for data ?
Can I get a copy of your assignment?
It's very hard to follow along without the materials
For a beginner that want to penetrate/transition to Data Analytics what books or subjects should I focus on? I do have basic excel knowledge and that's just about it. Thanks!
Hey there Mark!
I'd recommend learning about the basics of statistics as that is core to data analysis and machine learning. There are plenty of books out there, or even video series (Skillshare, Coursera, TH-cam) where you can get started on this.
Data becomes more fun when you seek out a dataset that is interesting to you! What I mean is: if you can ask basic data questions around a subject/topic you enjoy, you're more prone to seek out answers for something you already have interest in.
Start with Stats, move on to SQL, and then Python. My recommendation is to look at a job you'd want to have in 1-2 years, and see what skills would be necessary to land that job!
Thanks for the tips! I'll look into those!
How was the date/time conversion to something that can be summed/subtracted done? having trouble subtracting the date/times
Hello! Did you give datediff function a try?
Can we access this data? And how?
Can I have Data file?
Thanks for sharing. I have the same dataset for the interview and am getting the same numbers as you are showing in this video. Is it okay to follow your approach and present to them? I am sure they also know that the solution is already online for this. Wondering what's the catch here 😲
can you please share the link of dataset ?
I think its best to take what you learn in this video and try to apply your own approaches. I am sure creative is valued, this intent is to be a starting point :)
How did your interview go? I have this same data set exercise as I'm interviewing with a large food delivery app.
@@dannywallace1358 it went well. moved onto the next round.
@@learnanalyticsorg did you complete your analysis only in excel or did you use Postgres SQL
was the slide done in powerpoint?
Yes it was done in slides format.
Hello! I was given this case study as well, are you able to help me formulate the graphs? I'm having trouble.
What trouble are you facing?
Does anyone know how to convert the timestamps in excel to calculate the difference between timestamps? Any help would be appreciated!
What is the diffrence between customer placed order time vs placed order with restaurant time.? They both should be same right?
Hello, these can be different for example. Customer placed order time is when customer placed the order while restaurant order placed time is when the restaurant time of order actually goes through. It depends on how the dataset is good to check if they are different or same.
Thanks for sharing! Just out of curiosity did you pass this analytics test?
Yes
Can I have the dataset File?
Really helpful vid! How was the "45 min Delivery Time" report created? I'm trying to figure out the name to creat a similar one for practice.
Hey Mashiro! thanks for your question - we are trying something new and started a community page on Luma, let me know if you are interested to join and can ask questions there.
@@learnanalyticsorghi! Thanks for such a useful video! I’d like to join your community if it’s possible 🙏🏻
Thanks again for this AWESOME video! I have my assessment now and not the greatest with charts and graphs. Can anyone simply tell me how to manipulate the day and time fields to make pivot charts and graphs in excel ? I’m really struggling here.
happy to help, can you share your email and we can take it off.
@@learnanalyticsorg Hi, I am having the same issue with the timestamps in the pivot tables. Can you assist?
Hi @@learnanalyticsorg, would you be able to show me how to manipulate as well? Your help would be greatly appreciated!
@@dj-myle Hey we are trying something new and started a community page on Luma, let me know if you are interested to join and can ask questions there.
@@simplya1651 Hey there! we are trying something new and started a community page on Luma, let me know if you are interested to join and can ask questions there.
hey how can i get uber eats data pleasehelp
this was really helpful. Thanks.
thank you so much! Great video!
Thank you very much, its really helpful!
Glad it was helpful!
Please make more case studies.
Especially online shop and e-commerce commpanies
Can anyone complete this for me? I’ll pay to have this completed in the next 36 hours.
Thanks for sharing
I can't see the dataset on your Facebook?
Check out this persons github as well. ghayward.github.io/TipsAnalysis_June2018.html
Question: What is your tool in generating these insights?
His english is very good, he doesnt think before speaking
Upwork project sent me here, many thanks
Cool, what do you mean by Upwork project?
Beautfiful
I wish you could share the code as well. Otherwise really good work. :)
I dont have the code at hand, but hopefully it helped you!
1:38
I really doubt you passed this case. If restaurant 9 has such a high amount of daily average then how can restaurant 350 have higher average orders. it should be 9 or 20 or any other that generated higher revenue. if I take 30$ to be average order size then restaurant 350 does not even come close. The basic math is not sound
@@rontep6162 i actually got this case, merchant 9 has higher order volume and avg order amount as well. I also found the RFM of customers and clustered them and saw which region was better customer wise. I tried a few other things but did a lot of things similar to what is done in the video. But I was not taken to the next round. Very confused about this lol
Search a Great video
Thank you. We plan on creating another case study video soon. Stay tune.
Why can't I leave comments?
i think you are able to
Hi, for some reason when I comment on my laptop the comment is deleted. I just wanted to say it was an excellent video and I thought for the benefit of beginners or BI developers like myself wanting to transition to analytics, it would be great if you could do a follow-on video covering the many statistical concepts you implicitly relied on in this video. A question i had was on the last visualisation, have you split the data into quartiles ordered by delivery time (overall I assume ie placed to delivered), chosen the top 3 quartiles, and given the medians within those quartiles? And if yes, why did you choose to only show the top 3 rather than 4 quartiles and why did you find it of value to highlight in bold the second quartile (50%)? Thank you.
When I say a video on, what I mean was a video on WHY, I know what the median is I know what a quartile is etc
umm
You hesitate too much er er er it is difficult to understand
Do you mind sharing the link to your Facebook group, please? I am working on a similar exercise for big tech and would love to hear some feedback/insights.