Welcome to Privacy & Data Ethics! Today we're exploring one of the most critical challenges facing modern analysts: protecting individual privacy while delivering valuable insights.
Every data point represents a real person with rights and expectations about how their information is used.
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In one sentence, why does privacy matter in analytics?
Here's the reality: every time you analyze customer data, you're handling someone's personal information. Their shopping habits, location data, browsing history - all deeply personal details.
With great analytical power comes great responsibility to protect this trust.
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What's one type of personal data you handle regularly?
Privacy violations can destroy careers and companies. Target famously predicted a teenager's pregnancy before her father knew, creating a public relations nightmare and legal concerns.
The lesson? Analytical capability without ethical boundaries creates dangerous situations.
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What's another time analytics crossed a privacy line?
The challenge isn't avoiding data entirely - it's finding the sweet spot between valuable insights and individual privacy. You can analyze shopping patterns without knowing specific customers' names or addresses.
This balance is called "privacy-preserving analytics" and it's becoming essential for modern analysts.
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Can you name one insight you could generate without using personal identifiers?
Here are core privacy principles every analyst should know: Data minimization (collect only what you need), purpose limitation (use data only for stated purposes), and consent (people should know and agree to data use).
These aren't just legal requirements - they're ethical foundations for responsible analytics.
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