Is there a way to set the months values based on the end of month vs the first of the month. See this for reference to what I mean:
What you’re looking at there is “transaction drill-down” which is a nascent feature of ours, where you can drill-down into the component transactions of a certain GL code or data item. Right now it only works with a few select integrations (e.g. Gsheets/CSV, NetSuite) and we’re adding more to this list early next year.
So in answer to your question, if there were multiple transactions here, they would each show up as separate lines, so you could view all of the transactions here. It looks like your particular screenshot only has one transaction.
Does that answer your question?
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Sorry - I think I could have been a bit clearer.
What I’m referring to is that the model has granularity set to monthly. So I’m seeing months as columns. This is great, but I have a row which has a zero value as well as the db icon indicating that the value comes from a data source. The thing is that there should be a non-zero value here. I checked the “drill-down” view and its referencing a Nov 1st date for the November column. I just want to confirm that the column for the month of November is pulling data for the entire month of November and not data as of the 1st of November.
How the data comes in may vary as well whether its a balance sheet or income statement. I’m using an integration so maybe the Causal knows how to treat the data (e.g. income statement as transactions during a period, balance sheet as a snap shot at the end of the month).
Hey @roca - sounds like this is better dealt with via live chat in-app (top-right) 
Generally - data sources from ERPs will come in using the sum of all of the transactions during the month (unless of course it is a balance sheet, in which case we use the final balance). If you’re not seeing what you expect to see coming in from your data source/s - we can help you troubleshoot this better via live-chat as we can get support access to your account and look at it directly
@heidi_causal That makes sense! Thank you.