Expert insights on synthetic data

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Evaluating open-source tools for data masking

Can you use open-source tools to mask sensitive production data for use in testing and development? We explore the available options and weigh the pros and cons of relying on DIY data masking solutions.

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How to create realistic, safe, document-based test data for MongoDB

Technical deep dive
Technical deep dive

Generating high quality test data for MySQL through de-identification and synthesis

Data de-identification
Data de-identification
Test data management

Why I joined Tonic.ai: A business grad's perspective amid the pandemic

Tonic.ai editorial
Tonic.ai editorial

What is data synthesis, and why are we calling it data mimicking?

Technical deep dive
Technical deep dive

June ‘21 product update: support for all the databases

Product updates
Product updates

Data anonymization techniques defined: transforming real data into realistic test data

Technical deep dive
Technical deep dive

How to generate safe, useful test data for Amazon Redshift

Technical deep dive
Technical deep dive

5 traditional approaches to generating test data

Technical deep dive
Technical deep dive

Why I joined Tonic.ai: A software engineer's perspective

Tonic.ai editorial
Tonic.ai editorial

Creating realistic, secure test data for Databricks

Technical deep dive
Technical deep dive

Reverse engineering your test data: It’s not as safe as you think it is

Test data management
Test data management
Data de-identification
Data privacy

Why I joined Tonic.ai: A product manager's perspective

Tonic.ai editorial
Tonic.ai editorial

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Accelerate development with high-quality, privacy-respecting synthetic test data from Tonic.ai.Boost development speed and maintain data privacy with Tonic.ai's synthetic data solutions, ensuring secure and efficient test environments.