Hi all Im relatively new to PBI but know my way around quite well, but this has had me stumped all day!
I have a dataset of say 700 instances of client ativity over the last 12 months. each client has a unique id, each activity has a start and end date and each client could have several activities but only one can be active at a time, or they may have no active activities at all. i need a power bi measure to show me the number of open activities at the end of each month for the year 2024. The placement_start date must be before each month end, the placement_end date must be null OR after a month end and the client age must be under 18 at the end of a month. so for example one activity could span April to July where i would want to count the unique identifier, but then nothing from August onwards. I have a calendar table which calculates EOMONTH for reference, but its the monthly count that keeps failing. Open to any approach that would solve my issue. in reality i just a crosstab visual with months ends as columns and the count as the values - been a very frustrating day !
I have a dataset of say 700 instances of client ativity over the last 12 months. each client has a unique id, each activity has a start and end date and each client could have several activities but only one can be active at a time, or they may have no active activities at all. i need a power bi measure to show me the number of open activities at the end of each month for the year 2024. The placement_start date must be before each month end, the placement_end date must be null OR after a month end and the client age must be under 18 at the end of a month. so for example one activity could span April to July where i would want to count the unique identifier, but then nothing from August onwards. I have a calendar table which calculates EOMONTH for reference, but its the monthly count that keeps failing. Open to any approach that would solve my issue. in reality i just a crosstab visual with months ends as columns and the count as the values - been a very frustrating day !