3 Critical Data Anonymization Challenges Solved (with Eclipse Risk)
If you want to safely leverage the increasing value of your sensitive data by implementing data anonymization at scale, you’re likely facing one (or all) of these critical challenges:
Fortunately, software can help you overcome each of these challenges.
Find out how by joining Ron Kaine, Software Product Manager at Privacy Analytics, Srini Venkat, Senior Solutions Architect at Privacy Analytics, and David Onyschuk, Director of Customer Relationship Management and Data Access at Alberta Health, in this brief, informative on-demand webinar.
Hear first-hand how Alberta Health uses the powerful Eclipse software platform to respond to its many requests, creating high-quality, anonymized data that protects patient privacy and meets all regulatory requirements.
PLUS, you’ll get a live demo of our latest software release. Be among the first to see the most powerful, flexible, and user-friendly version of Eclipse to date.
Learn how your organization can:
Ron Kaine, Software Product Manager, Privacy Analytics
Srini Venkat, Senior Solutions Architect at Privacy Analytics
David Onyschuk, Director of Customer Relationship Management and Data Access, Alberta Health
Situation: California’s Consumer Privacy Act inspired Comcast to evolve the way in which they protect the privacy of customers who consent to share personal information with them.
Situation: Integrate.ai’s AI-powered tech helps clients improve their online experience by sharing signals about website visitor intent. They wanted to ensure privacy remained fully protected within the machine learning / AI context that produces these signals.
Situation: Novartis’ digital transformation in drug R&D drives their need to maximize value from vast stores of clinical study data for critical internal research enabled by their data42 platform.
Situation: CancerLinQ™, a subsidiary of American Society of Clinical Oncology, is a rapid learning healthcare system that helps oncologists aggregate and analyze data on cancer patients to improve care. To achieve this goal, they must de-identify patient data provided by subscribing practices across the U.S.
Situation: Needed to enable AI-driven product innovation with a defensible governance program for the safe and responsible use
of voice-to-text data under Shrems II.
This course runs on the 2nd Wednesday of every month, at 11 a.m. ET (45 mins). Click the button to register and select the date that works best for you.