Practical Data Privacy • Katharine Jarmul & Alyona Galyeva
This interview was recorded for the GOTO Book Club.
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Read the full transcription of the interview here
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Katharine Jarmul - Principal Data Scientist at Thoughtworks & Author of “Practical Data Privacy“
Alyona Galyeva - Principal MLOps & Data Engineer at Thoughtworks
RESOURCES
Katharine
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Alyona
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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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