As a measure, you could do something like below. I'm assuming that you have a model as follows:

• Fact: (Date, ID, Value)
• DimDate: (Date, ...)
• Rates: (ID, Rate)
• Dim: (ID, ...)

With these tables you'd have relationships as below:

• Dim -1:N-> Fact
• Dim <-1:1-> Rates
• DimDate -1:N-> Fact

With the model above, you could then build a visual of:

• Rows: DimDate[Date]
• Columns: Dim[ID]
• Values: [Value Or Rate Measure]

Value = SUM ( 'Fact'[Value] )

Rate = SUM ( 'Rates'[Rate] )

Value Or Rate Measure =
VAR Value = [Value]
RETURN
  IF ( ISBLANK ( Value ), [Rate], Value )

This might not do what you want for totals - you didn't specify. So if you need visual totals you might try the following:

Value or Rate - visual totals =
SUMX (
  CROSSJOIN ( VALUES ( 'Dim'[ID] ), VALUES ( 'DimDate'[Date] ) ),
  [Value Or Rate Measure]
)

You could also handle this in Power Query M, assuming you have the same tables I've described above. I'm assuming each table has an associated query of the same name.

let
    Source = Table.AddColumn(Dim, "Date", each DimDate[Date]),
    #"Expanded Date" = Table.ExpandListColumn(Source, "Date"),
    #"Merged Queries" = Table.NestedJoin(#"Expanded Date", {"id", "Date"}, Fact, {"ID", "Date"}, "Fact", JoinKind.LeftOuter),
    #"Expanded Fact" = Table.ExpandTableColumn(#"Merged Queries", "Fact", {"Value"}, {"Value"}),
    #"Merged Queries1" = Table.NestedJoin(#"Expanded Fact", {"id"}, Rates, {"ID"}, "Rates", JoinKind.LeftOuter),
    #"Expanded Rates" = Table.ExpandTableColumn(#"Merged Queries1", "Rates", {"Rate"}, {"Rate"}),
    #"Added Custom" = Table.AddColumn(#"Expanded Rates", "Value Or Rate", each if [Value] = null then [Rate] else [Value]),
    #"Removed Columns" = Table.RemoveColumns(#"Added Custom",{"Value", "Rate"})
in
    #"Removed Columns"

Here, we're doing something similar, but at a table level, instead of as a measure. We crossjoin Dim[ID] and DimDate[Date] to get a dense table of all date and ID combinations. Then we left join the original Fact table and the Rates table. Then we add a column that takes [Value] if it exists, or [Rate] if [Value] is null.

There is an ISBLANK function and a NOT function, so you can put them together:

IsNotBlank = NOT(ISBLANK())

You should in future share what code you have tried.

My New Column =
  IF( ISBLANK([A]) || ISBLANK([B]), 0, 1)

And if that doesn't provide the expected results, then maybe column A has empty string and not null. So then try:

My New Column =
  IF( ISBLANK([A]) || [A] = "" || ISBLANK([B]), 0, 1)