Partially Redacted: Data, AI, Security & Privacy

Partially Redacted brings together leaders in engineering, data, AI, security, and privacy to share knowledge, best practices, and real world experience.

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February 7, 2024

Learning and Sharing in Public with Dagster Lab's Pedram Navid

In this episode Sean is joined by Pedram Naveed, Head of Data Engineering at Dagster Labs. They discuss the unique challenges and opportunities in the realm of data engineering, particularly the culture of learning and sharing within the field.

January 31, 2024

Documentation Redaction with Hill Redaction's Zena Obebe

In this episode Zena Obebe, the founder of Hill Redaction Services, joins the show to discuss the critical role of document redaction in maintaining privacy and security.

January 24, 2024

Decoding Data Localization for Payments in India with Skyflow's Sanjeev Sharma

This episode provides a comprehensive overview of the evolving digital payment sector in India, emphasizing the importance of regulatory compliance for fostering innovation and security.

January 17, 2024

The State of Privacy Engineering with Saima Fancy, Jay Averitt, and Mira Olson

In this episode a stellar panel of privacy engineering experts delve into the evolving world of privacy engineering. The panel discusses the challenges and opportunities facing privacy engineers, with each guest offering insights from their unique vantage points.

December 6, 2023

Privacy’s Company-wide Connection with Privacy Engineering Leader Pramod Raghavendran

The conversation delves into the unique role of privacy engineers compared to security engineers, emphasizing collaboration between privacy and security teams. Pramod shares insights into how privacy functions intersect with security, governance, and data platforms.

November 15, 2023

Why PII Data Isolation Matters with Skyflow's Roshmik Saha

In this episode, Roshmik Saha, Co-founder (Engineering) at Skyflow, discusses the critical importance of Personally Identifiable Information (PII) data isolation. The principle is straightforward—separate sensitive and non-sensitive data for effective data governance and privacy.