Split amount between departments

I will give a step by step solution to this. I suggest you start with a blank Power BI file and start from scratch for better understanding.

Step 1: Add the DIMSplit table to your data model using the "New table" option using the following code.

DIMSplit =
DATATABLE (
    "ID", STRING,
    "Dep", STRING,
    "Share", INTEGER,
    {
        { "aaa", "90-1", "150" },
        { "aaa", "90-2", "150" },
        { "aaa", "90-3", "200" },
        { "bbb", "90-1", "50" },
        { "bbb", "90-2", "50" }
    }
)

Step 2: Add the "FACTTrans" table to your data model using the "New Table" option using the following code.

FACTTrans =
DATATABLE (
    "Date", DATETIME,
    "Amount", DOUBLE,
    "Dep", STRING,
    "SplitID", STRING,
    {
        { "01-01-2020", "10.000", "90-1", "aaa" },
        { "01-01-2020", "15.000", "90-1", "bbb" },
        { "01-01-2020", "25.000", "90-1", BLANK () },
        { "02-02-2020", "20.000", "90-1", "aaa" },
        { "03-03-2020", "30.000", "90-1", "bbb" }
    }
)

Step 3:  Add the "Expected Result" table to your data model using the "New Table" option using the following DAX code.

ExpectedResult =
VAR SumTable =
    SUMMARIZECOLUMNS ( FACTTrans[Date], DIMSplit[Dep], DIMSplit[ID] )
VAR EmptyIDTable =
    GENERATE (
        SUMMARIZECOLUMNS ( 'FACTTrans'[Date], DIMSplit[Dep] ),
        ROW ( "ID", BLANK () )
    )
RETURN
    UNION ( SumTable, EmptyIDTable )

Step 4: Add the following calculated columns to the "Expected Result" table using the following DAX codes.

Amt =
VAR CurrentDate = ExpectedResult[Date]
VAR CurrentDepartment = ExpectedResult[Dep]
VAR CurrentID = ExpectedResult[ID]
RETURN
    SUMX (
        FILTER (
            FACTTrans,
            FACTTrans[Dep] = CurrentDepartment
                && FACTTrans[Date] = CurrentDate
                && FACTTrans[SplitID] = CurrentID
        ),
        FACTTrans[Amount]
    )

DateIDAmount =
VAR CurrentDate = ExpectedResult[Date]
VAR CurrentID = ExpectedResult[ID]
VAR Sum1 =
    SUMX (
        FILTER (
            ExpectedResult,
            ExpectedResult[Date] = CurrentDate
                && ExpectedResult[ID] = CurrentID
        ),
        ExpectedResult[Amt]
    )
VAR Sum2 = ExpectedResult[Amt]
RETURN
    IF ( ISBLANK ( ExpectedResult[ID] ), Sum2, Sum1 )

PercentageSplit =
VAR CurrentID = ExpectedResult[ID]
VAR CurrentDep = ExpectedResult[Dep]
VAR DepIDAmount =
    SUMX (
        FILTER ( DIMSplit, DIMSplit[Dep] = CurrentDep && DIMSplit[ID] = CurrentID ),
        DIMSplit[Share]
    )
VAR IDAmount =
    SUMX ( FILTER ( DIMSplit, DIMSplit[ID] = CurrentID ), DIMSplit[Share] )
RETURN
    IF ( ISBLANK ( ExpectedResult[ID] ), 1, DIVIDE ( DepIDAmount, IDAmount, 0 ) )

FinalAmount =
ExpectedResult[DateIDAmount] * ExpectedResult[PercentageSplit]

Step 5: Add a matrix visual to your report and use the Expected Result table's date(month) and Department fields to column and rows respectively and add the "Final Amount" field to the "Values" section of the matrix which will give you the following result.

This is not an optimum solution, but nevertheless you will get the results and you can also see the intermediate results at every step. Later on, you may simplify the codes or rewrite the same using measures though that will be consuming your CPU power a lot if your dataset is quite large. 

Please let me know if you have any trouble understanding any of the DAX code snippets. By the way, there are no relationships between any of these tables.

Hi Anonymous 

Using a small bridge table, you can achieve the results using a measure itself instead of using the "Expected Result" calculated table and the other "calculated columns" in that table.

The 2nd solution using measure is as follows...

Prerequisite: Open a blank Power BI file and complete Step 1 & Step 2 mentioned earlier to create the "DIMSplit" and "FACTTrans" tables.

Step 3: Create a bridge table - Use calculated table / New table with the following DAX code.

IDs_BridgeTable = ALL(DIMSplit[ID])

Step 4: Create the following relationships.

IDs_BridgeTable[ID] -> DIMSplit[ID], One to Many, Active relationship

IDs_BridgeTable[ID] -> FACTTrans[SplitID], One to Many, Active relationship

DIMSplit[Dep] <-> FACTTrans[Dep], Many to Many, Inactive relationship

 Step 5: Create a Measure

ExpectedResult =
VAR IT_TABLE =
    ADDCOLUMNS (
        SUMMARIZE ( DIMSplit, DIMSplit[ID], DIMSplit[Dep] ),
        "ID_Dep_Amount", CALCULATE (
            SUMX ( FACTTrans, FACTTrans[Amount] ),
            CROSSFILTER ( DIMSplit[ID], IDs_BridgeTable[ID], BOTH )
        ),
        "ID_Total", CALCULATE ( SUMX ( DIMSplit, DIMSplit[Share] ), ALL ( DIMSplit[Dep] ) ),
        "ID_Dep_Share", CALCULATE ( SUMX ( DIMSplit, DIMSplit[Share] ) )
    )
VAR Res1 =
    SUMX ( IT_TABLE, [ID_Dep_Amount] * DIVIDE ( [ID_Dep_Share], [ID_Total], 0 ) )
VAR Res2 =
    CALCULATE (
        SUMX ( FILTER ( FACTTrans, FACTTrans[SplitID] = "" ), FACTTrans[Amount] ),
        USERELATIONSHIP ( DIMSplit[Dep], FACTTrans[Dep] )
    )
VAR Result = Res1 + Res2
RETURN
    Result

Step 6: Use a matrix visual and use DIMSplit[Dep] on Rows, FACTTrans[Date].Month on Columns, and the measure "Expected Result" created on Step 5 in the "Values" section of the matrix to get the following result.

The major difference between the earlier solution and this is that the earlier one is relying on calculated tables and calculated columns created using DAX and the result is stored in the data model in a separate table. But in this case, the result is calculated using only a measure without the need for any calculated table or calculated columns except for the bridge table in many to many relationship. We could have avoided the bridge table also, but it will make the measure more complicated.

You may try both approaches in your data model and use "Performance Analyser" to evaluate and compare the performance between both the approaches and its difference will be evident if you use a really large dataset.  It is up to you to decide between the two approaches.