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Extracting parts of a full name

You can use the Extract full name parts function to extract the different parts that make up a full name into different columns.

About this task

Applied on a column containing full names, this function is able to extract information on titles, first names, middle names, last names, suffixes and nicknames via an internally trained machine learning model. A confidence score is also added, that gives you an idea of the reliabilty of the extract process, based on that model.

In this example, you have received a dataset containing information about the subscribers of your online service, such as their full names, or subscription date. However, you need to export this data to a CRM solution and the full name format is not ideal for this task. To match the expected format of your CRM, you would prefer to have each part of your customers names displayed in dedicated columns. In order to achieve this, you will simply apply the Extract full name parts function to the column containing the customers names.


  1. Click the header of the Name column to select its content.
  2. In the functions panel, type Extract full name parts and click the result to open the options for the associated function.
  3. Select all the categories that you want to extract.
    In this example, leave all the checkbox selected. Each category will be extracted to a new column.
  4. Click Submit.


The different information that were part of the full names are extracted and displayed separately in new columns. The data is now properly formatted, which is much more practical for a future export to a CRM solution, or simply to apply filters and further work on the dataset.
Information noteTip: This transformation can also be performed by using the Automatically formatting data based on examples function.

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