Need Help writing a DAX Formula that returns distinct values based on max date

[CarMechanic]

Hello everyone, 
i need your help in writing a DAX Formula that returns distinct values for a row, based on max date that is smaller or equal to the value chosen in a slicer.

So i have a DataTable which is being loaded every day with new rows that have been updated. As you can see every change in the customer data is updated, by adding a new row with new loadtime.
Example:

Customer	Name	Postal Code	Loadtime
XXX	John	555 555	22.02.2023
XXX	John	666 666	20.02.2023
YYY	Elisabeth	444 444	22.02.2023
YYY	Emma	444 444	15.02.2023
ZZZ	Jules	111 111	11.02.2023

So if i choose a DATE with a SLICER : 22.02.2023 

I want to get is a table that looks like this:

Customer	Name	Postal Code	Loadtime
XXX	John	555 555	22.02.2023
YYY	Elisabeth	444 444	22.02.2023
ZZZ	Jules	111 111	11.02.2023

but if i change the slicer value to : 11.02.2023
i want a table to look like this:

Customer	Name	Postal COde	Loadtime
ZZZ	Jules	111 111	11.02.2023

I have tried different formulas but was unfortunately not successful. Would apperciate your help. 
Best Regards

[tamerj1]

Hi @CarMechanic 

the date slicer is coming from a dimDate table?

[CarMechanic]

yes

[tamerj1]

@CarMechanic 

Try by placing the following measure in the filter pane of the table visual and select "is" (1) then apply the filter

FilterMeasure =
INT (
MAX ( DataTable[Loadtime] )
= CALCULATE (
MAX ( DataTable[Loadtime] ),
ALLEXCEPT ( DataTable, DataTable[Name] ),
'Date'[Date] <= MAX ( 'Date'[Date] )
)
)

[FreemanZ]

hi @CarMechanic 

try to plot a table visual with Customer and Name columns and two measures like:

LoadtimeLast =

MAX(DataTable[Loadtime])

PostalCodeLast =

MAXX(

    FILTER(

        DataTable,

        DataTable[Loadtime]=[LoadtimeLast]

    ),

    DataTable[Postal Code]

)

[CarMechanic]

hello @FreemanZ ,
thanks for the fast response. 
Unfortunately this solution doesnt cover all the changes that can happen in a row. The tables i have posted are only examples. The real data rows consist of 30 columns with different attributes. Whenever one of the attributes changes, a new row with new loadtime will be added for a customer. So the solution must be more flexible than that. But thanks 🙂