Skip to main content
cancel
Showing results for 
Search instead for 
Did you mean: 

Join us for an expert-led overview of the tools and concepts you'll need to become a Certified Power BI Data Analyst and pass exam PL-300. Register now.

Reply
Anonymous
Not applicable

Transform and aggregate data

Hi all

 

This one has me stumped. What I want to do, is create a table with a customer case number, the customer's name and their forms of contact (phone, email and such like). It isn't working and it's because of the structure of my data, which looks like the below.

Capture.JPG

My case numbers are unique, my customer IDs are unique and everything relates well in PowerBI, but the way the data is formatted in table 3 is stuffing things up. 

 

What I want is for each customerID to be its own row, with the contact types to be columns of their own., like the below, if possible.

Capture2.JPG

The problem I have is that there are numerous customers with multiples of the same contact type, like 117 John A in my example above, so pivoting gives me errors. Short of asking my IT team to fix the format of the data set, is there anything I can do in PowerBI to fix it?

 

(Also, I should point out that the real tables are just under a million rows large.)

1 REPLY 1
Anonymous
Not applicable

Hi @Anonymous ,

 

You can refer to following sample to transform your query table based on grouping and splitcolumn functions:

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("i45WMjQ0V9JRCsjIz0sF0qampoZGxiZKsTrYZUyRZFxzEzNzgHRWfkZeokM6iKeXnJ8LVWGBqtfM3MISKmOJrDcxN7U42SEjvwRNOxZFaDYYGaDaYGxiagaVMUSVMbC0MMcuY2IMFEHIwC3MzE11yC8tycnPz4ZYGAsA", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type text) meta [Serialized.Text = true]) in type table [#"Customer ID" = _t, #"Contact Type" = _t, Detail = _t]),
    #"Changed Type" = Table.TransformColumnTypes(Source,{{"Customer ID", Int64.Type}, {"Contact Type", type text}, {"Detail", type text}}),
    #"Grouped Rows" = Table.Group(#"Changed Type", {"Customer ID"}, {{"Contents", each Table.Group(Table.RemoveColumns(_,{"Customer ID"}), {"Contact Type"}, {{"Content", each Text.Combine(_[Detail],","), type table}}), type table}}),
    #"Expanded Contents" = Table.ExpandTableColumn(#"Grouped Rows", "Contents", {"Contact Type", "Content"}, {"Contact Type", "Contents"}),
    #"Pivoted Column" = Table.Pivot(#"Expanded Contents", List.Distinct(#"Expanded Contents"[#"Contact Type"]), "Contact Type", "Contents"),
    #"Split Column by Delimiter" = Table.SplitColumn(#"Pivoted Column", "Phone", Splitter.SplitTextByDelimiter(",", QuoteStyle.Csv), {"Phone1", "Phone2"}),
    #"Split Column by Delimiter1" = Table.SplitColumn(#"Split Column by Delimiter", "Email", Splitter.SplitTextByDelimiter(",", QuoteStyle.Csv), {"Email1", "Email2"}),
    #"Changed Type1" = Table.TransformColumnTypes(#"Split Column by Delimiter1",{{"Phone1", Int64.Type}, {"Phone2", Int64.Type}, {"Email1", type text}, {"Email2", type text}})
in
    #"Changed Type1"

19.png

 

Regards,

Xiaoxin Sheng

Helpful resources

Announcements
Join our Fabric User Panel

Join our Fabric User Panel

This is your chance to engage directly with the engineering team behind Fabric and Power BI. Share your experiences and shape the future.

June 2025 Power BI Update Carousel

Power BI Monthly Update - June 2025

Check out the June 2025 Power BI update to learn about new features.

June 2025 community update carousel

Fabric Community Update - June 2025

Find out what's new and trending in the Fabric community.