Finding Change Types between tables

[Anonymous]

Hello,

I have two different data sets. One is previous week of sales data, while the other is current week of sales data. Between these weeks of sales data, there may be changes made to the revenue of a sale, or it's probability of occuring. I am trying to create a measure that tracks these changes, but I am struggling with finding the right DAX functions for the job. 

Using these two tables, I have created a table that contaings the sales IDs that have been changed (call this ChangesData) in either revenue or sales probability, along with their new revenue, and their new sales probability. I also have a table containing the old data that we are updating from (call this OldData), which contains the same fields. I would like to create a measure that track the specific changes to each ID (whether it be sales probability or sales revenue) between these two tables, resulting in something that looks like the table below. Keep in mind that the Probability column is a categorical variable which levels are (50%, 70%, and 100%).

Sales ID	Revenue	Prob.	Change Type	Resulting Change
123	$120,000	70%	Revenue	$20,000
456	$40,000	30%	Sale Probability	20% Increase

[amitchandak · Accepted solution]

@Anonymous , You merge in power query using ID and can create a column to  compare

Merge: https://radacad.com/append-vs-merge-in-power-bi-and-power-query

Power query column

if [Revenue] =  [New.Revenue] then "Match"  else "Different"

You can create a common ID tbale and compare meausre

if(Sum(Table1[Revenue]) = Sum(Table2[Revenue]) , "Match", "Different" )

https://amitchandak.medium.com/power-bi-when-i-asked-you-to-create-common-tables-a-quick-dax-solution-8e3eccb41bda

[Anonymous]

Looks like the power query column from M is working and giving me the correct results, but the measure using DAX is not working. No problem though, as the column from power query should suffice. Still wondering why power query and power BI don't share a language, but it seems like M is a lot less ambiguous. 

I appreciate your help.