What were you joining on @ntudev? Was it the Date by any chance? I've just tried conducting the join based on the S&P rating, and the values seem to line up fine. There's duplicates (2 of each) because you have 2 of each S&P rating in your 'Converted' tab:
Joining on Date (all dates are the same and so it'll join all Table 1 values to all Table 2 values giving 42*21 records):
How does this look @ntudev? I've just conducted one join at a time, as trying to conduct them both at once wouldn't work for records where the month/prior month are different. There's one instance (Prior Month S&P = 60) that doesn't match anything in the Dictionary table and so I've just unioned this record back on due to it getting dropped during the join (hence why the Prior Month Moody is null). If you want this to be dropped then obviously just remove the Union tool:
Like this @ntudev? I've only done 3 here hence why the others are just nulled because of the else null() part of my expression. If you wanted to do Prior month then you'd just do exactly the same. However, in cases like this it's definitely easier to use a join where you can instantly pull in the values based on a reference as writing out an if statement with so many different possibilities is time-consuming and not dynamic if more are added:
