Privacy Engineering

PrivacyEngineering is a hands-on guide to building a modern and flexible privacy program for your organization. It helps map essential legal requirements into practical engineering techniques that you can implement right away.

The book develops your strategic understanding of data governance and helps you navigate the tricky trade-offs between privacy and business needs. You''ll learn to spot risks in your own data management systems and prepare to satisfy both internal and external privacy audits. There''s no bureaucratic new processes or expensive new software necessary. You''ll learn how to repurpose the data and security tools you already use to achieve your privacy goals.

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.

Engineer privacy into your systems with these hands-on techniques for data governance, legal compliance, and surviving security audits.

In Privacy Engineering youwill 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.