Engineer privacy into your systems with these hands-on techniques for data governance, legal compliance, and surviving security audits.
In Privacy Engineering you will learn how to:
Classify data based on privacy risk
Build technical tools to catalog and discover data in your systems
Share data with technical privacy controls to measure reidentification risk
Implement technical privacy architectures to delete data
Set up technical capabilities for data export to meet legal requirements like Data Subject Requests (DSAR)
Establish a technical privacy review process to help accelerate the legal Privacy Impact Assessment (PIA)
Design a Consent Management Platform (CMP) to capture user consent
Implement security tooling to help optimize privacy
Build a holistic program that will get support and funding from the C-Level and board
Privacy Engineering teaches you to implement technical privacy solutions and tools at scale. You’ll learn from author Nishant Bhajaria, an industry-renowned expert who has overseen the privacy programs at Google, Netflix, and Uber. You’ll find technical methods that can be instantly applied to almost any system, and improve your user privacy without spiraling time and resource costs.
about the technology
Preserving the privacy of your users is essential for any successful business. Well-designed processes and data governance ensure that privacy is built into your systems from the ground up, keeping your users safe and helping your organization maintain compliance with the law.
about the book
Privacy Engineering is a hands-on guide to building a modern and flexible privacy program for your organization. You’ll create technical solutions that meet essential legal/compliance requirements and build a relationship of trust with your customers.
The book helps you implement scalable tools and methods to navigate the tricky trade-offs between privacy and business needs. You’ll quickly see how front-loading and automating your privacy program helps you spot risks in your own data management systems. Throughout, examples and architectures show you how to build the kind of privacy that both your customers and the law demand. There’s no bureaucratic new process; just hands-on technical solutions and smart repurposing of your existing security tools to achieve your privacy goals.
about the reader
about the author
Nishant Bhajaria leads the Technical Privacy and Strategy teams for Uber. He heads a large team that includes data scientists, engineers, privacy experts and others as they seek to improve data privacy for the customers and the company. His role has significant levels of cross-functional visibility and impact. Previously he worked in compliance, data protection, security, and privacy at Google. He was also the head of privacy engineering at Netflix. He is a well-known expert in the field of data privacy, has developed numerous courses on the topic, and has spoken extensively at conferences and podcasts.
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Provides a clear and thorough explanation of the how and the why of data privacy pitched at a level which isn't too technical, yet has a sufficient level of detail to allow for interpretation of implementation.
Really interesting subject matter. The author provides relevant examples and obviously has a lot of direct experience.
A great resource on approaching data privacy.
The best parts are the personal elements added to the narrative. I also enjoyed the case studies that help to illustrate the examples provided throughout.