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.

Try this below measure. Remember, this is not a replacement to the original column or value. But you can use this measure in table or other visual to show "No Vendor" where there is no data in the original column. This way you can keep original and customize both data.

vendor_name = 

var current_row_name = MIN(table_name[Name])

RETURN 
IF(
    current_row_name = BLANK(), 
    "No Vendor", 
    current_row_name
)

If you need a calculated column, you can try this below code-

vendor_name_column = 

var current_row_name = table_name[Name]

RETURN 
IF(
    current_row_name = BLANK(), 
    "No Vendor", 
    current_row_name
)