The heavily cross-dependent nature of privacy requires a holistic privacy engineering strategy based on data mapping, data classification, and data inventory to quantify privacy risks, build and enforce automated controls, and support privacy-compliant workflows in an interconnected tech ecosystem.

In this IAPP Privacy Engineering KNet session, we will focus on data classification. We’ll discuss different classification schemes and approaches to data segmentation, as well as strategies to tackle unstructured data, collaborate on data handling with internal stakeholders, explore access options, and learn how to kick off and maintain the data classification process. Panelists will share challenges they have encountered in their data governance journey and how they addressed them, whether by using comprehensive tools available on the market or by developing in-house solutions. After the main panel, registrants are invited to share their experiences and approaches in small working groups under Chatham House rules. Bring your questions, share your experience, and contribute to the growing privacy engineering community in the Bay Area!

March 22 at Santa Clara University from 5-7:30 pm PT

Speakers:

• Abhi Sharma, Co-Founder and Co-CEO, Relyance AI
• Nishant Bhajaria, Privacy Engineering Lead, Uber
• Tarana Damania, Sr. Director, Privacy Engineering at StockX

Moderator: Hoang Bao, Privacy & Data Protection Senior Leader, Google, Member of the IAPP Privacy Engineering Advisory Board

Welcoming words from IAPP: Nandita Rao, Head of Technical Privacy & Governance, DoorDash, Member of the IAPP Privacy Engineering Advisory Board

Welcoming words by Santa Clara University: Irina Raicu, Director of the Internet Ethics Program at the Markkula Center for Applied Ethics, Santa Clara University

March 22 at Santa Clara University from 5-7:30 pm PT

Register via this link: IAPP - Event