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Erase

Goal

The erase Work Tasks is well suited to all cases where you need to repeatedly mask/delete a subset of the database e.g. processing "Forget me"-requests

  • erase Work Tasks works across tables, and help maintain consistency

Identifying data that needs anonymization

You will primarily anonymize Personally Identifiable Data and Linkable Data. In addition, you may need to anonymize business critical data.

Personally Identifiable Information Examples

  • Names: first, middle and lastname, usernames, aliases
  • Addresses: home address, email address, IP address
  • Phone numbers: mobile numbers, fixed numbers
  • Personal identification numbers: passport number, driver’s license, credit/debit card, Tax Identification Number, patient ID number
  • Biometric data: photos, x-rays, fingerprints, retina scans, voice signatures

Quasi Identifier Examples

  • Date of birth
  • Race
  • Gender
  • Business telephone number
  • Place of birth
  • Religion
  • Educational information
  • Event based information

Work Task erase in Ano

In erase Work Tasks, you can use the mask rule strategy. In addition you can [cascade](../../rules(cascade) the referenced tables to mask or delete the corresponding records.

Parameters

erase Work Tasks use parameters to mask specific entries across the database.

With one parameter the syntax is:

where "IDColumn = %PARAMETER%

With many parameters, %PARAMETER% gets numbered (e.g. %PARAMETER1%), and the sequence must match the parameter sequence defined in the WHERE clause. E.g.:

where "(_HOTEL_ID_ = %PARAMETER1% AND ROOMCATEGORY_ID = %PARAMETER2% AND FROMDATE = '%PARAMETER3%')"

Visit the rules section for more information on how to write erase task rules.

Ereasing

task <TaskGroupName>
{
    erase <table> <WorkTaskName> where "ColumnName = %PARAMETER%"
        mask <column> <RuleName>
            <rule-logic>
        mask <column> <RuleName>
            <rule-logic>
        mask <column> <RuleName>
            <rule-logic>
}