Data protection and privacy frameworks adopted around the globe are generally established around some shared core principles. These principles are what guide organizations when processing personal data and underline many of the requirements found in modern privacy law.
This eBook will take a closer look at the principles found under:
When the GDPR was passed in 2016, it presented seven key principles for processing personal data that placed specific requirements on organizations. While the CCPA (as amended) does not specifically outline data processing principles, some of the obligations imposed on businesses and the rights warranted to California residents can be mapped against the data processing principles of the GDPR. Similar principles can be found under the EU-US DPF and this eBook will consider those principles, and where appropriate, the supplemental principles found in the framework.
Download this ebook to further understand these principles and to compare their similarities and differences.
Checklist
Self-certify for the EU-US DPF framework and comply with its seven core principles with this checklist.
eBook
The EU-US DPF represents an important mechanism for US-based companies to lawfully transfer personal data form the EU to the US. Use this eBook to learn more about how to self-certify with the framework and its seven core principles.
Infographic
The EU-US Data Privacy Framework is based upon seven core principles that organizations must comply with to certify with the framework.
Webinar
A webinar discussion of significant points and implications of the new UK-US Data Bridge.
Webinar
Join us for an expert panel as we discuss the finalized EU-US Data Policy Framework and what it means for organizations managing international data transfers.
Webinar
Join us for this webinar as we break down the May 22, 2023 DPC Meta decision and cover the key takaways for EU-US data transfers.
Webinar
Understand common scenarios for applying data access governance within your business and key considerations for evaluating open access risk.