What is Fake Data?

First off, why do we need fake data?

The answer is simple: to respect and protect the privacy of real data. Sure, there’s a lot of real data out there, but we shouldn’t be using it however we please.

Where do we need fake data?

There are many use cases. Here are the ones we focus on at Tonic.ai:

Software development, testing, and QA

ML model training

Data analysis

Sales demos

So, what do we mean by fake data?

Here are some terms you may have heard:

Test data

Anonymized data

De-identified data

Masked data

Encrypted data

Generated data

Synthesized data

Mimicked data

Lots of words with lots of meanings, but at a high level:

It’s all fake.

The difference lies in the approach. Not all fake data is created equally.

How should you fake it?

You should fake your data according to:

Your use case

The degree of privacy you need to achieve

The degree of utlity you want to preserve

Fact is, not all real data is created equally. Data exists on a spectrum. Your approach to faking it should too.

Faking data with Tonic.ai

Our platform offers all the fake data solutions you need in one place. Mix and match advanced de-identification, synthesis, and subsetting techniques to service all of your data’s use cases as they each need to be handled.

Fake your data to achieve the right degree of privacy and utility for each data point in your database.

How are you looking to fake it? Whatever your answer is, we can make it happen.

Tell me more

Fake your world a better place

Enable your developers, unblock your data scientists, and respect data privacy as a human right.

Book a Demo

Start Your Free Trial

Real Fake Data

First off, why do we need fake data?

Where do we need fake data?

So, what do we mean by fake data?