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Handling PII Information in Databricks
A Story to Start With: The Data Disaster
You’re a data engineer enjoying a quiet Friday afternoon when your phone buzzes. It’s your manager, in full panic mode, screaming, “Our customer data has been leaked!” Names, addresses, and payment details, everything.
The company’s Twitter feed is a war zone, the legal team is in DEFCON 1, and the CEO’s face looks like they’ve bitten into a lemon.
The best part? The breach happened because someone left a Spark notebook wide open with PII unmasked.
Could this be you? Let’s make sure it never is.
In the world of data, PII (Personally Identifiable Information) is like that VIP guest at a party. Everyone knows they’re important, but you need to handle them with care, or the party could be over before it starts.
Databricks, the cloud-based data platform, offers powerful tools for working with data at scale. But when it comes to PII, power must meet caution, or else you might just get your name etched into the GDPR wall of fame, for all the wrong reasons.
So, how do you work with PII in Databricks without ending up on a regulator’s naughty list?
Let’s dive into this step by step, with some real-world examples.
