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Anonymous's avatar
Anonymous
Not applicable
2 years ago
Solved

Creating dynamic measures to calculate duration between different timestamps

Dear all,

 

I have a database with logs of clients going through different stages of a process.

Each process has timestamp indicating the date when the single client has reached that stage of the process.

I want to create in DAX a dynamic measure that would allow users to choose the stages they want to calculate a lag time between. E.g.: one might be interested to investigate how many days (on average) elapse between date 1 and date 0, or between date 2 and date 0, and so on...

 

I tried using field parameters for start date and arrival date, in order for the user to just choose in a filter the starting point and the arrival point of the measure, which would be ideal for me. Nonetheless, it seems I can't be able to get this to work.

 

How would you proceed?

 

Thanks in advance for your kind help.

Giorgio

  • Anonymous's avatar
    Anonymous
    2 years ago

    HI Anonymous,

    I'd like to suggest you convert the table records to do complex unpivot column operation on these status and date fields:

    Full query:

    let
        Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [SNDG = _t, #"Data 0: Inizio monitoraggio" = _t, #"1: Contatto cliente" = _t, #"Data 1: Contatto cliente" = _t, #"2: Rintraccio" = _t, #"Data 2: Rintraccio" = _t, #"3: Analisi posizione e condivisione strategia" = _t, #"Data 3: Analisi posizione e condivisione strategia" = _t, #"4: Delibera" = _t, #"Data 4: Delibera" = _t]),
        #"Changed Type" = Table.TransformColumnTypes(Source,{{"SNDG", Int64.Type}, {"Data 0: Inizio monitoraggio", type text}, {"1: Contatto cliente", type text}, {"Data 1: Contatto cliente", type text}, {"2: Rintraccio", type text}, {"Data 2: Rintraccio", type text}, {"3: Analisi posizione e condivisione strategia", type text}, {"Data 3: Analisi posizione e condivisione strategia", type text}, {"4: Delibera", type text}, {"Data 4: Delibera", type text}}),
        fxTrans= (tb as table) =>
            let 
                #"Unpivoted Columns" = Table.UnpivotOtherColumns(tb, {}, "Attribute", "Value"),
                #"Added Custom" = Table.AddColumn(#"Unpivoted Columns", "Step", each Text.Combine(List.Select(Text.ToList([Attribute]), each Value.Is(Value.FromText(_), Int32.Type )))),
                #"Grouped Rows2"= Table.Group(#"Added Custom", {"Step"}, {{"Count", each Table.Transpose(Table.SelectColumns(_,{"Value"})), type table }}),
                #"ExpandTableColumn" = Table.ExpandTableColumn(#"Grouped Rows2", "Count", {"Column1", "Column2"}, {"Status", "Date"})
            in
                #"ExpandTableColumn",
        #"Grouped Rows" = Table.Group(#"Changed Type", {"SNDG", "Data 0: Inizio monitoraggio"}, {{"Content", each fxTrans(Table.RemoveColumns(_,{"SNDG", "Data 0: Inizio monitoraggio"})), type table }}),
        #"Expanded Content" = Table.ExpandTableColumn(#"Grouped Rows", "Content", {"Step", "Status", "Date"}, {"Step", "Status", "Date"})
    in
        #"Expanded Content"

    After these steps, you can simply use Dax expression with current group field value(SNDG) and steps as conditions. Then you can use them to find out correspond date values and calculated in DATEDIFF function.

    Regards,

    Xiaoxin Sheng

3 Replies

  • Anonymous's avatar
    Anonymous
    Not applicable

    Hi Anonymous ,

    Can you please share a pbix or some dummy data that keep the raw data structure with expected results? It should help us clarify your scenario and test to coding formula.

    How to Get Your Question Answered Quickly  

    Regards,

    Xiaoxin Sheng

  • Anonymous's avatar
    Anonymous
    Not applicable

    Here is the dummy data I'm starting from.

    As you can see, there are several steps of the process, and each step has a datestamp (Data 1, Data 2, Data 3, etc.)
    My measure would ideally use DATEDIFF or a similar function but the starting and end datestamps should be variable or subject to user decision.

     

    Thanks for your help!

    SNDGData 0: Inizio monitoraggio1: Contatto clienteData 1: Contatto cliente2: RintraccioData 2: Rintraccio3: Analisi posizione e condivisione strategiaData 3: Analisi posizione e condivisione strategia4: DeliberaData 4: Delibera
    105/01/2023Positivo05/02/2023  Consensual Liquidation22/04/2023Approvata03/05/2023
    218/01/2023Positivo17/02/2023  Judicial02/04/2023Approvata13/05/2023
    302/01/2023Positivo17/02/2023  DPO13/04/2023Approvata07/05/2023
    414/01/2023Positivo23/02/2023  Judicial25/04/2023Non approvata17/05/2023
    501/01/2023Positivo18/02/2023  Rimodulazione28/04/2023Approvata05/05/2023
    608/01/2023Positivo07/02/2023  Rimodulazione05/04/2023Approvata27/05/2023
    706/01/2023Positivo13/02/2023  Rimodulazione24/04/2023Approvata19/05/2023
    812/01/2023Positivo22/02/2023  Consensual Liquidation01/04/2023Approvata16/05/2023
    903/01/2023Positivo18/02/2023  Judicial14/04/2023Non approvata02/05/2023
    1025/01/2023Positivo24/02/2023  Piano di rientro light03/04/2023  
    1124/01/2023Positivo03/02/2023  Judicial27/04/2023Non approvata17/05/2023
    1214/01/2023Positivo05/02/2023  Rimodulazione28/04/2023Approvata01/05/2023
    1322/01/2023Positivo10/02/2023  Rimodulazione23/04/2023Approvata14/05/2023
    1422/01/2023Positivo20/02/2023  Consensual Liquidation02/04/2023Approvata15/05/2023
    1526/01/2023Positivo12/02/2023  Rimodulazione05/04/2023Approvata01/05/2023
    1615/01/2023Positivo01/02/2023  DPO05/04/2023Approvata07/05/2023
    1702/01/2023Positivo24/02/2023  DPO01/04/2023Non approvata20/05/2023
    1820/01/2023Positivo01/02/2023  Piano di rientro light09/04/2023  
    1927/01/2023Positivo07/02/2023  Piano di rientro light26/04/2023  



     

    • Anonymous's avatar
      Anonymous
      Not applicable

      HI Anonymous,

      I'd like to suggest you convert the table records to do complex unpivot column operation on these status and date fields:

      Full query:

      let
          Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("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", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [SNDG = _t, #"Data 0: Inizio monitoraggio" = _t, #"1: Contatto cliente" = _t, #"Data 1: Contatto cliente" = _t, #"2: Rintraccio" = _t, #"Data 2: Rintraccio" = _t, #"3: Analisi posizione e condivisione strategia" = _t, #"Data 3: Analisi posizione e condivisione strategia" = _t, #"4: Delibera" = _t, #"Data 4: Delibera" = _t]),
          #"Changed Type" = Table.TransformColumnTypes(Source,{{"SNDG", Int64.Type}, {"Data 0: Inizio monitoraggio", type text}, {"1: Contatto cliente", type text}, {"Data 1: Contatto cliente", type text}, {"2: Rintraccio", type text}, {"Data 2: Rintraccio", type text}, {"3: Analisi posizione e condivisione strategia", type text}, {"Data 3: Analisi posizione e condivisione strategia", type text}, {"4: Delibera", type text}, {"Data 4: Delibera", type text}}),
          fxTrans= (tb as table) =>
              let 
                  #"Unpivoted Columns" = Table.UnpivotOtherColumns(tb, {}, "Attribute", "Value"),
                  #"Added Custom" = Table.AddColumn(#"Unpivoted Columns", "Step", each Text.Combine(List.Select(Text.ToList([Attribute]), each Value.Is(Value.FromText(_), Int32.Type )))),
                  #"Grouped Rows2"= Table.Group(#"Added Custom", {"Step"}, {{"Count", each Table.Transpose(Table.SelectColumns(_,{"Value"})), type table }}),
                  #"ExpandTableColumn" = Table.ExpandTableColumn(#"Grouped Rows2", "Count", {"Column1", "Column2"}, {"Status", "Date"})
              in
                  #"ExpandTableColumn",
          #"Grouped Rows" = Table.Group(#"Changed Type", {"SNDG", "Data 0: Inizio monitoraggio"}, {{"Content", each fxTrans(Table.RemoveColumns(_,{"SNDG", "Data 0: Inizio monitoraggio"})), type table }}),
          #"Expanded Content" = Table.ExpandTableColumn(#"Grouped Rows", "Content", {"Step", "Status", "Date"}, {"Step", "Status", "Date"})
      in
          #"Expanded Content"

      After these steps, you can simply use Dax expression with current group field value(SNDG) and steps as conditions. Then you can use them to find out correspond date values and calculated in DATEDIFF function.

      Regards,

      Xiaoxin Sheng