Description

Welcome back to the Klaviyo Data Science podcast! This episode, we dive into…

What are data privacy and security?

Data privacy and security are huge and hugely important topics — in all likelihood, you already know a little about them if you’re reading this intro. But they are both crucial to any good data science work, and this month we explore the fundamentals of both topics: why data privacy and security are necessary to deliver the value you promise your customers, who they matter the most to, and how to build privacy and security into your own data science work. The panel includes some of the foremost experts on the topics at Klaviyo from data science, engineering, and security and risk governance, so you’ll get to hear about these topics from a variety of angles, including:

• How approaches to data privacy that seem intuitive can fail, and fail spectacularly
• The consequences of not taking privacy and security carefully enough
• How to make people actively want to work within the security environment you set up

“The worst case is that you violate your customers’ trust. And if you think about personal relationships you have where someone has violated your trust, it’s really hard to build that back.”

- Dom Lombardi, Security Risk and Compliance Manager

Learn More

• Privacy and security failures mentioned in the episode
  
   — The SWIFT hack of the Bank of Bangladesh
  
   — The CafePress data breach
• Differential privacy
  
  —Overview:  A non-technical primer from Nissim et al. 
  
   — Example: Apple’s DP Sketch algorithm
  
   — Example: Google’s RAPPOR
• Data Privacy
  
   — The Harvard Business Review’s New Rules of Data Privacy

For the full show notes, see the writeup on Medium.