Data Privacy, Video Edition

Data Privacy, Video Edition

by Nishant Bhajaria
Released February 2022
Publisher(s): Manning Publications
ISBN: None

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Video description

In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.

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.

About the Technology
Data privacy is essential for any business. Data breaches, vague policies, and poor communication all erode a user’s trust in your applications. You may also face substantial legal consequences for failing to protect user data. Fortunately, there are clear practices and guidelines to keep your data secure and your users happy.

About the Book
Data Privacy: A runbook for engineers teaches you how to navigate the trade-off s between strict data security and real world business needs. In this practical book, you’ll learn how to design and implement privacy programs that are easy to scale and automate. There’s no bureaucratic process—just workable solutions and smart repurposing of existing security tools to help set and achieve your privacy goals.

What's Inside
  • Classify data based on privacy risk
  • Set up capabilities for data export that meet legal requirements
  • Establish a review process to accelerate privacy impact assessment
  • Design a consent management platform to capture user consent


About the Reader
For engineers and business leaders looking to deliver better privacy.

About the Author
Nishant Bhajaria leads the Technical Privacy and Strategy teams for Uber. His previous roles include head of privacy engineering at Netflix, and data security and privacy at Google.

Quotes
I wish I had had this text in 2015 or 2016 at Netflix, and it would have been very helpful in 2008–2012 in a time of significant architectural evolution of our technology.
- From the Foreword by Neil Hunt, Former CPO, Netflix

Your guide to building privacy into the fabric of your organization.
- John Tyler, JPMorgan Chase

The most comprehensive resource you can find about privacy.
- Diego Casella, InvestSuite

Offers some valuable insights and direction for enterprises looking to improve the privacy of their data.
- Peter White, Charles Sturt University

Publisher resources

View/Submit Errata

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

Product information

  • Title: Data Privacy, Video Edition
  • Author(s): Nishant Bhajaria
  • Release date: February 2022
  • Publisher(s): Manning Publications
  • ISBN: None