I have a bunch of property data I am getting each month for multiple properties.
My end goal is to build monthly summaries for each property like this:
Eventually I’d like to put these calculations in some type of chart to compare these metrics at these levels.
Is there a way to run these calculations in Airtable dynamically? Maybe using scripts?
My goal is to create these charts where users can assess these trends.
Any advice would be greatly appreciated!
I’m no scripting guy, so people smarter than me will no doubt be able to help you with that, but imo it can be done with the Airtable functions. It depends on how you want to get the data I think.
For example, you could just group the summaries on type (1br,2br,studo) and then have the average shown for a “price” field. You also could make a simple filtered view to show the units that are available (and maybe have the sum showed for a “number of available units” field). With the chart app, you can probably make the needed chart(s) to compare these things.
But as I said, that’s the easy answer :slightly_smiling_face:
I’m a coder; everything looks like a nail for my collection of hammers. And despite this, I agree.
But, it all depends on whether there are aggregations that require multiple passes or other complexities.
I would look at the count field and roll ups. Ideally you want the summaries in a new table so that reporting and views are a bit simpler to manage.
A lot depends on how you structure your data. Formula fields and rollup fields can go a long way in calculating averages and amounts.
Another issue is generating “monthly” reports. Do you generate the report each month based on all available data? Or do you want to generate a report for each month using only that month’s data? In the latter case, you need a way of determining the month for an individual record and consolidating information for that month, either through linked records or some sort of code.
There are three reasons we capture data:
Data modelling is a delicate dance that must embrace each of these key objectives. If you have a data model that cannot effectively embrace the requirements of #3, you need to fix that in the model with deference to the limitations of the database platform, …OR… you must backfill the weaknesses with script automation.
That @kuovonne - for being so young, she speaks the wisdom of a very old and deeply experienced database designer.