Data Privacy. A runbook for engineers

Аннотация

Engineer privacy into your systems with these hands-on techniques for data governance, legal compliance, and surviving security audits. In Data Privacy 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 Asset 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. Data Privacy teaches you to design, develop, and measure the effectiveness of privacy programs. You’ll learn from author Nishant Bhajaria, an industry-renowned expert who has overseen privacy at Google, Netflix, and Uber. The terminology and legal requirements of privacy are all explained in clear, jargon-free language. The book’s constant awareness of business requirements will help you balance trade-offs, and ensure your user’s privacy can be improved without spiraling time and resource costs.