Difference between dates
Best Answer

One thing you can do is group the datediff into buckets using a beastmode case statement. Like for instance if I was looking at the date difference from when a customer clicked a photo and when they edited a photo and I knew my average was 30 days, I may group the number of times the action happened into buckets and look at that over time. For instance, I may group the number of customers who did that action in 07 days, 814 days, 1521 Days ... 60+ Days. You can then look at the counts or percentages over time to see if they are increasing or decreasing.
One problem with averages is you could have large outliers that can skew your data. If you have 10 customers and 9 completed the action in 1 day versus a customer who it took 100 days to complete, your average would be 10.9 days. If you look at the data in buckets you could potentially say 90% of customers complete the action in 07 days, which tells a much different story than it takes 10.9 days on average to complete this action.
Hope this helps.
Thanks,
Brian
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Answers

Hi Prajwal,
Could you please provide a little more context to your problem and maybe an example?
I am hesitant to say just create a beast mode using the DATEDIFF() function then bring that into your Y Axis, changing the calculation to "Average," if your problem happens to be more complex than that.
Thanks,
Brian
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Hey,
So I have to create a visualization to find how long it is taking between 2 events. For example, what is the number of days between when a photo is clicked and when it is edited and how this trend is changing over time?
I did create a Beast mode DATEDIFF() function calculation on the yaxis with date on the xaxis. I also grouped the dates into months so that I can find the average difference in days for each month. I used line chart.
Is there anything more that I can do to leverage the power of DOMO and create an even powerful viz?
Regards,
Prajwal
0 
One thing you can do is group the datediff into buckets using a beastmode case statement. Like for instance if I was looking at the date difference from when a customer clicked a photo and when they edited a photo and I knew my average was 30 days, I may group the number of times the action happened into buckets and look at that over time. For instance, I may group the number of customers who did that action in 07 days, 814 days, 1521 Days ... 60+ Days. You can then look at the counts or percentages over time to see if they are increasing or decreasing.
One problem with averages is you could have large outliers that can skew your data. If you have 10 customers and 9 completed the action in 1 day versus a customer who it took 100 days to complete, your average would be 10.9 days. If you look at the data in buckets you could potentially say 90% of customers complete the action in 07 days, which tells a much different story than it takes 10.9 days on average to complete this action.
Hope this helps.
Thanks,
Brian
**Please mark "Accept as Solution" if this post solves your problem
**Say "Thanks" by clicking the "heart" in the post that helped you.
**Please mark "Accept as Solution" if this post solves your problem
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Hi,
Thanks a lot for that. I will try it out.
Wrt outliers, that was precisely what I was thinking. Average is definitely not a good indicator when there are outliers. I could use median but I could not find median aggregation in DOMO.
May be grouping them in to buckets will help deal with outliers much better.
Regards,
Prajwal
0
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