Transformers

Transformers are a set of configurations applied to files that are uploaded into Marketing Cloud Intelligence Data Pipelines. Transformers are used to alter the structure of the data files in order to pull the exact data sets you need. They instruct the platform as to what data table must be extracted from your source file allowing you to manipulate the file structure.

For example, if your source file contains extra or missing information— missing headers, multiple sheets, and extra rows or columns. The transformers allow you to manipulate the file structure, for example inserting a default header where it’s missing so that data is pulled correctly. Transformers are applied during the preview source step when creating or editing a TotalConnect data stream. Four transformers are applied to your data automatically: File, Table, Headers, and Totals. Add additional transformers for more advanced file structure manipulations.

• MDP Apply File Transformers
  Use file transformers when you want to transform a file that has special characteristics like uncommon delimiters, multiple sheets, or specific file encoding. For example, if a file uses ~~ as the delimiter instead of a comma or a tab, use the file transformer to specify the custom delimiter so that you can map the file correctly.
• MDP Apply Table Transformers
  The table transformer enables you to customize a table’s start and end rows and columns.
• MDP Apply Header Transformers
  If you want to customize the header structure when headers aren’t available or span multiple rows, you can use a header transformer. For example, if a file has a two-line header that must be combined into one row.
• MDP Total Rows Transformers
  Use the total rows transformer when you want to change the default behavior of Marketing Cloud Intelligence Data Pipelines to strip out “totals” rows from all files. For example, if a file has non-additive measurements, and you want only the totals row mapped, use this transformer.
• MDP Transpose Transformers
  Use a transpose transformer when you want to reconstruct a flat-file format by translating columns of data into rows. For example, if a file has three conversion types in three separate columns that you want to aggregate into “total conversions,” they must be transposed into rows from columns. A column of data in a flat-file corresponds to a field that could be mapped in the Marketing Cloud Intelligence Data Pipelines data model. So anytime you can streamline the number of potential mapped fields, you free up fields that can be used for other dimensions or measurements. After transpose settings are set for a data stream, new files uploaded to the data stream automatically inherit the predefined pattern that was specified upon initial integration.
• MDP Apply Unnest Transformers
  The unnest transformer enables you to transform concatenated values into separate rows. The measurement values linked to the nested row are duplicated to each new row. For example, If there are three values, comma-separated, and one field must be broken out into individual rows of data, this transformer creates individual rows for each value in that field.
• MDP Apply Pivot Transformers
  The pivot transformer can transform values from selected columns into new individual columns, which then contain aggregated values for the measurements.
• MDP Apply PGP/GPG Decryptor Transformers
  You can use the PGP/GPG transformer when you want to decrypt uploaded encrypted files with a PGP/GPG decrypting tool.
• MDP Apply Data Transformer
  Select the data transformer checkbox to manipulate actual data contained in the files you upload.