Practical Data Privacy • Katharine Jarmul & Alyona Galyeva

GOTO - The Brightest Minds in Tech

This interview was recorded for the GOTO Book Club.
gotopia.tech/bookclub

Read the full transcription of the interview here

Katharine Jarmul - Principal Data Scientist at Thoughtworks & Author of "Practical Data Privacy"
Alyona Galyeva - Principal MLOps & Data Engineer at Thoughtworks
RESOURCES
Katharine
twitter.com/kjam
linkedin.com/in/katharinejarmul
kjamistan.com
probablyprivate.com
Alyona
github.com/alyonagalyeva
linkedin.com/in/alyonagalyeva

DESCRIPTION
Integrating privacy-enhancing technologies into software applications is an imperative step for safeguarding user data and adhering to regulatory requirements in the realm of software development. However, prior to implementation, it is vital for development teams to grasp the potential pitfalls associated with incorporating privacy technology. They must also appreciate the significance of iterative processes and the necessity of collaborative efforts to ensure compliance.
Furthermore, achieving the delicate equilibrium between privacy and utility is of paramount importance. Organizations must meticulously fine-tune privacy settings, tailoring them to suit specific use cases.
Additionally, alongside this core evaluation criterion, considerations such as speed and computational efficiency may enter the equation, demanding expertise in privacy engineering for successful implementation at scale.
Katharine Jarmul, the author of "Practical Data Privacy," spoke to Alyona Galyeva from PyLadies Amsterdam, during which she unveiled a slew of open-source libraries and practical examples for implementing privacy technology. Katharine also explored how developers can proactively guarantee that their data science projects prioritize security by design and uphold privacy by default.
The interview is based on the book "Practical Data Privacy"
RECOMMENDED BOOK
Katharine Jarmul • Practical Data Privacy
Katharine Jarmul & Jacqueline Kazil • Data Wrangling with Python
Katharine Jarmul & Richard Lawson • Python Web Scraping
Yehonathan Sharvit • Data-Oriented Programming
Zhamak Dehghani • Data Mesh
Eberhard Wolff & Hanna Prinz • Service Mesh
Piethein Strengholt • Data Management at Scale
Martin Kleppmann • Designing Data-Intensive Applications

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Розділи

1. Intro (00:00:00)

2. Behind the scenes of "Practical Data Privacy" (00:01:33)

3. The need for demystifying privacy engineering (00:03:26)

4. Tuning data protection with differential privacy (00:08:27)

5. Structuring the privacy process (00:14:55)

6. Differential privacy applied (00:22:14)

7. Vector of attack in differential privacy (00:33:10)

8. Outro (00:38:34)