We've identified the 9 most common ways your synthetic data can fail you — and the solutions you need to ensure safety and utility in your test data.
There are wrong ways to fake your data. These data generation pitfalls can break your testing or, worse, leak sensitive data into unsecured environments.
Join us for this live webinar to gain insight into generating realism in:
- time series data and event pipelines,
- categorical data distributions,
- consistency in JSON blobs,
- outliers at risk of re-identification,
- and working across SQL and NoSQL databases.
Don't fail at faking it. We're here to help.
Be sure to download the companion ebook Fake Data Anti-patterns for the fullest experience.
Enable your developers, unblock your data scientists, and respect data privacy as a human right.