Top 5 Drawbacks to Using Only Data Masking

Top 5 Drawbacks to Using Only Data Masking

Data Masking is Just Not Enough

Although data masking and de-identification are often grouped together for discussion, the two use different approaches in making data anonymous. Furthermore, masking and de-identification deal with different identifiers in a dataset. Masking is used to anonymize direct identifiers while de-identification is used to anonymize quasi-identifiers. In practice, masking and de-identification should be used together to optimize the balance between protecting privacy and maintaining the usefulness of the data. This paper explores the major limitations of using data masking on its own, without de-identification.

In this white paper, learn exactly what the top 5 drawbacks are to using only data masking and why they need to be avoided.

Turn Privacy into Business Potential Across Your Data Life Cycle Join the 100s of companies that have benefitted from our solutions. Planning Acquiring/ Collecting…
Privacy Analytics You’re not just protecting data. .   Scroll for more Health Data Privacy Clinical Trial Transparency Enterprise Data Privacy Effective data privacy…
Here are key highlights from May 2022 detailing global news and regulatory updates. US & Canada Canada’s Privacy Commissioner to leave his post June…
Previous
Next

Archiving / Destroying

Are you unleashing the full value of data you retain?

Your Challenges

Do you need help...

OUR SOLUTION

Value Retention

Client Success

Client: Comcast

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.

Evaluating

Are you achieving intended outcomes from data?

Your Challenge

Do you need help...

OUR SOLUTION

Unbiased Results

Client Success

Client: Integrate.ai

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.

Accessing

Do the right people have the right data?

Your Challenges

Do you need help...

OUR SOLUTION

Usable and Reusable Data

Client Success

Client: Novartis

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.

 

Maintaining

Are you empowering people to safely leverage trusted data?

Your Challenges

Do you need help...

OUR SOLUTION

Security / compliance efficiency

CLIENT SUCCESS

Client: ASCO’s CancerLinQ

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.

 

Acquiring / Collecting

Are you acquiring the right data? Do you have appropriate consent?

Your Challenge

Do you need help...

OUR SOLUTIONS

Consent / Contracting strategy

Client Success

Client: IQVIA

Situation: Needed to ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR. 

 

Planning

Are You Effectively Planning for Success?

Your Challenges

Do you need help...

OUR SOLUTION

Build privacy in by design

Client Success

Client: Nuance

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.

 

Join the next 5 Safes Data Privacy webinar

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.