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Anonymous's avatar
Anonymous
Not applicable
6 years ago
Solved

Combining text data from 3 different databases

Hi all,   I am stuck with combining the data of three datasets. I've been looking around for similar cases, but haven't found what I'm looking for yet. I'm afraid I can't share the file due to the ...
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  • v-lid-msft's avatar
    v-lid-msft
    6 years ago

    Hi Anonymous ,

     

    We can create a calculated colmun using following formula to meet your requirement:

     

    Column = 
VAR n = [Article number]
VAR t1 =
    FILTER (
        'Article description',
        'Article description'[Article number] = n
            && 'Article description'[Language] = "English"
    )
VAR t2 =
    FILTER ( 'Article database', 'Transaction data'[Article number] = n )
VAR articlename =
    IF (
        COUNTROWS ( t1 ) > 0,
        MAXX ( t1, [Article name] ),
        MAXX ( t2, [Article name] )
    )
RETURN
    n & " " & articlename

     


    BTW, pbix as attached.

     

    Best regards,

    Community Support Team _ Dong Li
    If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Anonymous's avatar
Anonymous
Not applicable
5 years ago

v-lid-msft , I've got a bit similar problem as last year. Would you be able to help me out again?
I now have a column with 'art. number + name'  and a column with 'language code'.
Example:

Art.nr+name        LanguageCode

12345 Bread        EN
12345 Brot           DE
12345 Brood        NL

I have 2 problems:
1. I would like to split the first column at the first space in 2 columns: Article number; Article name (I don't have a separate article name column now, but can be very usefull for various tables)

2. I would like to make a new column with (1x each unique) art.number & 1 language of choice.

E.g. if I filter for English, only 12345 Bread remains from this list (and all the unique other codes + english description). 

 

I've been trying, but without succes. Can you give me a hand again? Would be much appreciated!