Data Privacy: A Runbook for Engineers

Bhajaria, Nishant

  • 出版商: Manning
  • 出版日期: 2022-02-15
  • 定價: $1,750
  • 售價: 9.5$1,663
  • 貴賓價: 9.0$1,575
  • 語言: 英文
  • 頁數: 384
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1617298999
  • ISBN-13: 9781617298998
  • 立即出貨



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

"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." 
Neil Hunt, Former CPO, Netflix

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.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

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.

Editorial Reviews


"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 Chief Product Officer, Netflix 

"Nishant's timely and powerful book is a must read, must share and must commit to action gem in the hands of every leader in the digital economy of today and forevermore.  We can't uninvent fire & won't stop observing and sharing data."
—Michelle Finneran Dennedy, former Chief Privacy Officer at Cisco and author of The Privacy Engineer's Manifesto

"An indispensable guide for practitioners -- engineers, data scientists, and attorneys -- on how to build a world-class privacy program."
—Matthew G Olsen, former Uber Chief Trust and Security Officer.

"Bhajaria's succinct and practical frameworks are required reading for anyone who needs to quickly understand how privacy is operationalized to reduce business and engineering friction."
-—Melanie Ensign, Founder and CEO, Discernible Inc and advisor to "The Rise of Privacy Tech"

"The best parts are the personal elements you add to the narrative. I also enjoyed the case studies that help to illustrate the examples you provide throughout."
—Ayana Miller, Privacy & Data Protection Advisor, former Privacy specialist at the Federal Trade Commission (FTC) 

"Your guide to building privacy into the fabric of your  organization." 
—John Tyler, Vice President at JPMorgan Chase

"The most comprehensive resource you can find about privacy."
—Diego Casella, Sr. Software Engineer at InvestSuite

"Offers some valuable insights and direction for enterprises looking  to improve the privacy of their data." 
—Dr. Peter White, Lecturer at Charles Sturt University


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.


1 Privacy engineering: Why it’s needed, how to scale it
2 Understanding data and privacy
3 Data classification
4 Data inventory
5 Data sharing
6 The technical privacy review
7 Data deletion
8 Exporting user data: Data Subject Access Requests
9 Building a consent management platform
10 Closing security vulnerabilities
11 Scaling, hiring, and considering regulations