CRUX: The Agile Approach to External Data Integration
Immuta: eBook – Guide to Preserving Privacy in Data Science
In the last two decades, the ability to collect personal information on individuals has opened up a new frontier, fueling innovation and enabling companies and organizations to deliver better, more personalized services at scale. But innovation carries risks, and this new frontier is rife with them. Organizations must proactively develop controls and processes to guard personal data in order to have sustained success in a data-driven world.
- examines methods for transforming data in a manner that protects the privacy of individuals while preserving utility
- provides an overview of the challenges and opportunities of privacy-aware analytics
- equips data analysts and scientists with a framework for implementing anonymization techniques within data projects.