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Telephone Numbers

The Telephone Numbers masking option is used for generating missing telephone numbers or masking the existing ones. This masking is applicable only on string and numeric datatypes column.

This type of masking can generate telephone numbers in in six different formats as per the selected option, if column datatype is string. In case of numeric datatype, telephone numbers are generated in one format only, i.e., Digits Only, and other listed options are disabled.

The formats in this masking specify the components of a phone numbers, i.e., area code, exchange, subscriber number, based on the type of separation you opt.

  1. Digits Only - If you opt for this option, then telephone numbers are generated without any separation that can specify the component of phone number.

    E.g., with reference to the below image, the phone numbers are separated with space in the dataset and there are two records where phone number is missing. To generate the missing value and mask the existing one, you can apply Telephone Numbers masking.


    Here, we’ve applied Digits Only masking which generates fake telephone values for both existing and missing fields. Also, the generated value has no format specified i.e., dash or space.

    In the below image, the missing values has been generated for employees Fathi and Didier and the existing values for other employees has been masked.

  2. Space Separation - If you opt for this option, then telephone numbers are generated with space separation that can specify the component of phone number such as the area code, exchange numbers, etc. In the Space Separation, the format of the number looks like ‘xxx xxx xxxx’.

    E.g., with reference to the below image, the phone numbers are specified without any separation in the dataset. To mask the existing one, you can apply Telephone Numbers masking with Space Separation option.


    Here, we’ve applied Space Separation masking which generates fake telephone values for both existing and missing fields.

    In the below image, the existing values for all employees has been masked. For Instance, the actual contact number of Enid has been masked with value ‘935 995 7522’ which was originally ‘7608449182’.

  3. Dash Separation - If you opt for this option, then telephone numbers are generated with space separation that can specify the component of phone number such as the area code, exchange numbers, etc. In Dash Separation, the format of the number looks like ‘xxx-xxx-xxxx’.

    E.g., with reference to the below image, the existing phone numbers are in space separation format in the dataset. To mask the existing one, you can apply Telephone Numbers masking with Dash Separation option.


    Here, we’ve applied Dash Separation masking which generates fake telephone values for both existing and missing fields, if any.

    In the below image, the existing values for all employees has been masked. For Instance, the contact number for Fathi has been masked with value ‘355-589-8983’ which was originally ‘260 978 9154’ in the dataset.

  4. Standard - If you opt for this option, the telephone numbers are generated in a standard format that specify the component of phone number such as the area code, exchange numbers, etc. In Standard, the format of the number looks like ‘(xxx) xxx-xxxx’.

    E.g., with reference to the below image, the data is in dash separation format in the dataset. To mask the existing one, you can apply Telephone Numbers masking with standard option.


    Here, we’ve applied Standard masking which generates fake telephone values for both existing and missing fields, if any.

    In the below image, the existing values for all employees has been masked. For Instance, the contact number for Enid has been masked with value ‘(792) 877-7427’ which was originally ‘323-876-8585’ in the dataset.

  5. Standard Without Space - If you opt for this option, the telephone numbers are generated in a standard format without space and specify the component of phone number such as the area code, exchange numbers, etc. In this format, the number looks like ‘(xxx)xxx-xxxx’.

    E.g., with reference to the below image, the data is in dash separation format in the dataset. To mask the data, you can apply Telephone Numbers masking.


    Here, we’ve applied Standard Without Space masking which generates fake telephone values for both existing and missing fields, if any.

    In the below image, the existing values for all employees has been masked. For Instance, the contact number for Enid has been masked with value ‘(020)589-8408’ which was originally ‘323-876-8585’ in the dataset.

  6. Dot Separated - If you opt for this option, the telephone numbers are generated in a dot separated format. In this format, the number looks like ‘xxx.xxx.xxxx’.

    E.g., with reference to the below image, the data is in standard without space format in the dataset. If you want to generate a dot formatted data, then apply Telephone Numbers masking.


    Here, we’ve applied Dot Separated masking which generates fake telephone values for both existing and missing fields, if any.

    In the below image, the existing values for all employees has been masked. For Instance, the contact number for Enid has been masked with value ‘595.582.7561’ which was originally ‘(840)646-8345’ in the dataset.


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