Protect Your Data by Design - Creating a Data Masking Strategy

This session covers common obstacles to data masking and how to plan a strategy for protecting data in pre-production environments. It emphasizes understanding and cataloging data, creating a shared taxonomy, and tracing data flows to guide masking decisions.

Syllabus

Intro
So is this a 'vendor session'...?
Goal
Why do we need to protect data? (1)
Where do data breaches come from?
Why do we need to protect data? (3)
Regulations have
There's lots of ways to protect data!
What is Data Masking?
Control available datasets
Static vs Dynamic Data Masking
So technically, is this masked?
What do we have to think about first?
We require Realism
4) words on realism
Data depends on Data
Perfect normalization is a dream
It needs to be fast!
BUT... We can't mask if we don't know what we have!
Understand your data
Catalog your data
Create a business-wide accepted taxonomy
Use THIS for your decisions
know how data moves
Now we know where the risk is. Let's protect it
Mask once and cascade