I have a budget dataset with the following columns:
_Account
_Subsidiaries
_Department
_Doctor
_Location (Not in Use)
_Headcount Resources
_Placeholder 4
_Year
_Period
_Scenario
_Currency
_Measure
_value
I have an actuals dataset with the following columns:
Appointment Date
Status
Appointment Type
Patient Account Number
Location
Provider
I want to be able to overlay budget and compare it to actuals. This seems simple enough in theory, but the differing datasets is causing difficulties:
- The end goal at the highest level is to see how many appointments we have scheduled and how many we have budgeted within the same simple view. I.e. We have 100 surgeries scheduled but 200 budgeted.
- The actuals dataset is obviously at a day level. (I.e. June 20), where the Budget is at a monthly level (I.e. June Month)
- The actuals dataset is at a singular level (i.e. 1 surgery), where the budget is grouped/pivoted to the time frame (i.e. 500 surgeries (for Month of June)).
- There are multiple Providers, multiple Locations, multiple Appointment Types, Multiple Statuses, etc….. It's not as simple as a 1:1 join.
- Finally, the datasets have unneeded information. The actuals dataset includes "Status" data of "Cancelled", which doesn't need to be included since it doesn't actually exist and didn't happen. The budget dataset includes different "Measures" that affect the "Values". If the Measure is "Units" then the Values is interpreted as surgeries. If the Measure is "Value" then the Values is interpreted as cash revenue.
I attempted to solve this with a separate question (see link below), but didn't provide enough context to allow for more tailored assistance.
Cheers to anyone that can help tackle this - this is a huge initiative that would be a big win for the team.