Forum Discussion
Employee age structure
Hi Jan,
Please download the solution from the attachment.
1. Create an independent table [Ages] in case that no all the ages are listed. Don't establish a relationship.
Ages = GENERATESERIES(20, 65, 1)
2. Create a what-if parameter from 0 to the number you need, which means the years. For example, 1 year later.
Measure = SUMX ( 'Table1', IF ( [Age] = MIN ( Ages[Value] ) - [Parameter Value], 1, 0 ) )
3. Create a visual.
Best Regards,
Dale
Hi Jan,
Please download the solution from the attachment.
1. Create an independent table [Ages] in case that no all the ages are listed. Don't establish a relationship.
Ages = GENERATESERIES(20, 65, 1)
2. Create a what-if parameter from 0 to the number you need, which means the years. For example, 1 year later.
Measure = SUMX ( 'Table1', IF ( [Age] = MIN ( Ages[Value] ) - [Parameter Value], 1, 0 ) )
3. Create a visual.
Best Regards,
Dale
Thank you, that's it!
Could you please explain to me how the measure actually works? I cannot seem to wrap my head around it. Specifically the condition:
[Age] = min(Ages[Value]) - [Parameter Value]
Why are you searching for the minimum Ages Value and then subtracting the parameter?
Thank you. I might be too dumb.
Jan
Hi Jan,
That's a challenge for me, too. The dates and time are dynamic.
1. The min() function aims to match the ages in the X-axis. Because there isn't a relationship. Actually, it returns a single value. Let's have a look at the example in the last snapshot, it's 27 in the lower visual (the red rectangle).
2. The [Parameter Value] is 0 at first. That means we don't add any years. It's simple in this scenario. When the age equals the X-axis value, we tag it 1. Or it's 0. Finally, we sum them up.
3. When we add some years to see the forecast, the X-axis is the ages in the future. So we need to delete the [Parameter Value] to match the actual age in the data table. For example, how many people will be 27 in one year later? We need to count the people who are 26 now. So it's 27 in the X-axis while it's 26 in the data table (the source).
Best Regards,
DaleThank you so much. I think I get it now:)