Data Privacy, Video Edition

Table of contents

1. Part 1. Privacy, data, and your business
2. Chapter 1. Privacy engineering: Why it’s needed, how to scale it
3. Chapter 1. How data flows into and within your company
4. Chapter 1. Why privacy matters
5. Chapter 1. Privacy: A mental model
6. Chapter 1. How privacy affects your business at a macro level
7. Chapter 1. Privacy tech and tooling: Your options and your choices
8. Chapter 1. What this book will not do
9. Chapter 1. How the role of engineers has changed, and how that has affected privacy
10. Chapter 1. Summary
11. Chapter 2. Understanding data and privacy
12. Chapter 2. This could be your company
13. Chapter 2. Data, your business growth strategy, and privacy
14. Chapter 2. Examples: When privacy is violated
15. Chapter 2. Privacy and the regulatory landscape
16. Chapter 2. Privacy and the user
17. Chapter 2. After building the tools comes the hard part: Building a program
18. Chapter 2. As you build a program, build a privacy-first culture
19. Chapter 2. Summary
20. Part 2. A proactive privacy program: Data governance
21. Chapter 3. Data classification
22. Chapter 3. Why data classification is necessary
23. Chapter 3. How you can implement data classification to improve privacy
24. Chapter 3. How to classify data with a focus on privacy laws
25. Chapter 3. The data classification process
26. Chapter 3. Data classification: An example
27. Chapter 3. Summary
28. Chapter 4. Data inventory
29. Chapter 4. Machine-readable tags
30. Chapter 4. Creating a baseline
31. Chapter 4. The technical architecture
32. Chapter 4. Understanding the data
33. Chapter 4. When should you start the data inventory process?
34. Chapter 4. A data inventory is not a binary process
35. Chapter 4. What does a successful data inventory process look like?
36. Chapter 4. Summary
37. Chapter 5. Data sharing
38. Chapter 5. How to share data safely: Security as an ally of privacy
39. Chapter 5. Obfuscation techniques for privacy-safe data sharing
40. Chapter 5. Sharing internal IDs with third parties
41. Chapter 5. Measuring privacy impact
42. Chapter 5. Privacy harms: This is not a drill
43. Chapter 5. Summary
44. Part 3. Building tools and processes
45. Chapter 6. The technical privacy review
46. Chapter 6. Implementing the legal privacy review process
47. Chapter 6. Making the case for a technical privacy review
48. Chapter 6. Integrating technical privacy reviews into the innovation pipeline
49. Chapter 6. Scaling the technical privacy review process
50. Chapter 6. Sample technical privacy reviews
51. Chapter 6. Summary
52. Chapter 7. Data deletion
53. Chapter 7. What does a modern data collection architecture look like?
54. Chapter 7. How the data collection architecture works
55. Chapter 7. Deleting account-level data: A starting point
56. Chapter 7. Deleting account-level data: Automation and scaling for distributed services
57. Chapter 7. Sensitive data deletion
58. Chapter 7. Who should own data deletion?
59. Chapter 7. Summary
60. Chapter 8. Exporting user data: Data Subject Access Requests
61. Chapter 8. Setting up the DSAR process
62. Chapter 8. DSAR automation, data structures, and data flows
63. Chapter 8. Internal-facing screens and dashboards
64. Chapter 8. Summary
65. Part 4. Security, scaling, and staffing
66. Chapter 9. Building a consent management platform
67. Chapter 9. A consent management platform
68. Chapter 9. A data schema model for consent management
69. Chapter 9. Consent code: Objects
70. Chapter 9. Other useful capabilities in a CMP
71. Chapter 9. Integrating consent management into product workflow
72. Chapter 9. Summary
73. Chapter 10. Closing security vulnerabilities
74. Chapter 10. Protecting privacy by managing perimeter access
75. Chapter 10. Protecting privacy by closing access-control gaps
76. Chapter 10. Summary
77. Chapter 11. Scaling, hiring, and considering regulations
78. Chapter 11. The privacy engineering domain and skills
79. Chapter 11. Privacy and the regulatory climate
80. Chapter 11. Summary