Dealing with PII
Talking to a prospect today about PII - identifying it on data loaded into the system and then processing it - eg reporting its presence.
Comments appreciated
Steve
Best Answer
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These rules could also be incorporated into a workflow that automatically pushes the data through a validate step before doing any processing (and pop a Fire Event step afterward to alert key people when PII is detected).
The passing rows could then be passed through to subsequent processing, with the results information being fed into a PII report (either within Aperture Data Studio, or outside into a visualisation tool like Tableau / PowerBI).
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Answers
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Hey Steve,
First step is to figure out specifically what data elements you want to identify under 'PII' (e.g. name, address, email, dob, telephone, credit card, cookie etc).
Then build rules that help you detect each type of PII data using the functions available within the product. Some useful functions include:
- Contains Match - references a lookup table to find presence of certain words/values/formats/terms in each field (in the example below I used this function to identify Names by doing a lookup to a table of Titles)
- Matches Expression - utilise some of the regular expressions that the product ships with to identify some common types of data (e.g. postcode, telephone number, email address, credit card). Equally you can add your own, in the glossary (e.g. loyalty card number, cookies etc)
- Matches Format - define your own formats in the function (e.g. dates)
Using a combination of these functions will allow you to not only detect PII data (true/false), but categorise it (e.g. email, tel etc.) and locate it (e.g. which fields contain it).
See below for a screenshot of a quick example I just built:
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