Data Masking with Data Products
Sensitive data in testing environments and analytical data stores has to be masked, and that’s a fact. Especially in today’s unforgiving regulatory environment.
Perhaps the biggest problem facing traditional data masking tools is to ensure referential integrity of data across many different systems. Will the masking of PII data applied to the CRM, for example, be consistent across the billing, marketing, and technical support systems?
That’s where data products come in.
A data product would integrate and deliver all the data related to customers, from all underlying source systems, to all downstream systems, while masking sensitive data along the way.
But the referential integrity challenge remains.
Consider an entity-based data product that would unify a single customer’s data, and mask it as a single unit. Instead of masking data by tables and systems, an entity-based data product masks the data by, well, the entity – one customer’s data, across all systems, at a time.
In this scenario, not only would it be straightforward to ensure the customer’s masked data is identical and consistent across all systems, it would also be easy to execute in flight (rather than in batch).
In short, an entity-based data?product approach?would simplify the complexity inherent in data masking, assuring all customer PII data is:
Digital Growth Team Lead at K2View
2 年Some great reads in this Newsletter
Rabbi/ Eductor/ Overachiever, Out-of-the-box thinker, Proven record of exceptional ROI
2 年WOW! That technology of the Micro-Db for every single business entity means that you can encrypt every single customer/card etc. and therefore eliminate in essence massive data breaches! Go K2View!