The data transformation guides

Learn how to make your sensitive data usable in software and AI development through our comprehensive guides.
Data in action: how quality data can revolutionize the financial industry
Data in action: how quality data can revolutionize the financial industry
Developer productivity
AI in healthcare: data privacy and ethics concerns
AI in healthcare: data privacy and ethics concerns
Data privacy in AI
How to gather test data for testing purposes: a guide
How to gather test data for testing purposes: a guide
Test Data Management
Data in action: how quality data can transform the healthcare industry
Data in action: how quality data can transform the healthcare industry
Developer productivity
How data quality issues can slow down product development
How data quality issues can slow down product development
Developer productivity
How better data helps you do more
How better data helps you do more
Developer productivity
The importance of using reliable datasets for testing, QA, and development
The importance of using reliable datasets for testing, QA, and development
Test Data Management
A comprehensive guide to ethical fine-tuning of Large Language Models
A comprehensive guide to ethical fine-tuning of Large Language Models
AI model training
Privacy by Design in generative AI: building secure and trustworthy AI systems
Privacy by Design in generative AI: building secure and trustworthy AI systems
Data privacy in AI
How secure, high-quality data can accelerate your time to market
How secure, high-quality data can accelerate your time to market
Developer productivity
Advanced techniques for generating synthetic test data
Advanced techniques for generating synthetic test data
Data synthesis
Creating an enterprise test data strategy with Tonic Structural
Creating an enterprise test data strategy with Tonic Structural
Tonic Structural how-tos
Balancing compliance and data utility in AI model training
Balancing compliance and data utility in AI model training
AI model training
Integrating Tonic Structural with your existing tech stack
Integrating Tonic Structural with your existing tech stack
Tonic Structural how-tos
The importance of AI Compliance for your business
The importance of AI Compliance for your business
Data privacy in AI
How to overcome common data provisioning challenges
How to overcome common data provisioning challenges
Test Data Management
AI & data privacy: what every organization needs to know
AI & data privacy: what every organization needs to know
Data privacy in AI
Use cases for de-identified datasets
Use cases for de-identified datasets
Data de-identification
Synthesizing healthcare data for AI model training, with HIPAA Expert Determination
Synthesizing healthcare data for AI model training, with HIPAA Expert Determination
AI model training
Data privacy vs security: understanding the difference
Data privacy vs security: understanding the difference
Data de-identification
Unstructured data management: what it is and how to manage it
Unstructured data management: what it is and how to manage it
Test Data Management
RAG chatbot: What it is, benefits, challenges, and how to build one
RAG chatbot: What it is, benefits, challenges, and how to build one
AI model training
Best LLM security tools: features & more
Best LLM security tools: features & more
Data privacy in AI
Understanding LLM security risks (with solutions)
Understanding LLM security risks (with solutions)
Data privacy in AI
Understanding data redaction: methods, use cases, and benefits
Understanding data redaction: methods, use cases, and benefits
Data privacy in AI
What is retrieval augmented generation? The benefits of implementing RAG in using LLMs
What is retrieval augmented generation? The benefits of implementing RAG in using LLMs
AI model training
The hidden value of test data: a case study on tech debt & business value
The hidden value of test data: a case study on tech debt & business value
Test Data Management
Data anonymization vs data masking: is there a difference?
Data anonymization vs data masking: is there a difference?
Data de-identification
Data de-identification in the healthcare industry
Data de-identification in the healthcare industry
Data de-identification
Static vs dynamic data masking
Static vs dynamic data masking
Data de-identification
Data anonymization: a guide for developers
Data anonymization: a guide for developers
Data de-identification
De-identifying your unstructured data in Databricks with Tonic Textual
De-identifying your unstructured data in Databricks with Tonic Textual
Tonic Textual how-tos
Quickly building training datasets for NLP applications
Quickly building training datasets for NLP applications
AI model training
How to generate synthetic data: a comprehensive guide
How to generate synthetic data: a comprehensive guide
Data synthesis
Data de-identification in the finance industry
Data de-identification in the finance industry
Data de-identification
Custom sensitivity rules to automate sensitive data detection
Custom sensitivity rules to automate sensitive data detection
Tonic Structural how-tos
Optimizing Oracle database management, part 3: benefits & best practices of Ephemeral data environments
Optimizing Oracle database management, part 3: benefits & best practices of Ephemeral data environments
Test Data Management
Optimizing Oracle database management, part 2: CDB, PDB, & key features
Optimizing Oracle database management, part 2: CDB, PDB, & key features
Test Data Management
Optimizing Oracle database management, part 1: common challenges & innovative solutions
Optimizing Oracle database management, part 1: common challenges & innovative solutions
Test Data Management
Ensuring data privacy with privacy rankings in Tonic Structural
Ensuring data privacy with privacy rankings in Tonic Structural
Tonic Structural how-tos
The role of Ephemeral environments in QA
The role of Ephemeral environments in QA
Test Data Management
Understanding automated data redaction
Understanding automated data redaction
Data de-identification
Guide to data privacy compliance for financial institutions
Guide to data privacy compliance for financial institutions
Data synthesis
The role of NER in GDPR compliance and beyond
The role of NER in GDPR compliance and beyond
Data privacy in AI
Security for Tonic.ai cloud products
Security for Tonic.ai cloud products
Tonic Structural how-tos
Top 5 trends in enterprise RAG
Top 5 trends in enterprise RAG
AI model training
What is model hallucination?
What is model hallucination?
AI model training
Understanding named entity recognition (NER) models
Understanding named entity recognition (NER) models
AI model training
What is a database on demand?
What is a database on demand?
Test Data Management
Safeguarding data privacy while using LLMs
Safeguarding data privacy while using LLMs
Data privacy in AI
What is data de-identification?
What is data de-identification?
Data de-identification
How to create database subsets for Ephemeral environments
How to create database subsets for Ephemeral environments
Tonic Ephemeral how-tos
Understanding model memorization in machine learning
Understanding model memorization in machine learning
Data privacy in AI
Using Tonic Structural and the Safe Harbor method to de-identify PHI
Using Tonic Structural and the Safe Harbor method to de-identify PHI
Tonic Structural how-tos
Maintaining data relationships in Structural generation output
Maintaining data relationships in Structural generation output
Tonic Structural how-tos
7 test data pitfalls in software development
7 test data pitfalls in software development
Test Data Management
Integrating Tonic Structural into your data refresh and CI/CD pipelines
Integrating Tonic Structural into your data refresh and CI/CD pipelines
Tonic Structural how-tos
Guide to test data automation
Guide to test data automation
Test Data Management
Guide to synthetic test data generation
Guide to synthetic test data generation
Data synthesis
How to prevent data leakage in your AI applications with Tonic Textual and Snowpark Container Services
How to prevent data leakage in your AI applications with Tonic Textual and Snowpark Container Services
Tonic Textual how-tos
How to automatically redact sensitive text data In JSON format
How to automatically redact sensitive text data In JSON format
Tonic Textual how-tos
De-identifying free-text data in Snowflake using Tonic Textual
De-identifying free-text data in Snowflake using Tonic Textual
Tonic Textual how-tos
Tonic vs Delphix vs K2View vs IBM Optim. A full comparison.
Tonic vs Delphix vs K2View vs IBM Optim. A full comparison.
Test Data Management
Using custom models in Tonic Textual to redact sensitive values in free-text files
Using custom models in Tonic Textual to redact sensitive values in free-text files
Tonic Textual how-tos
Guide to test data management
Guide to test data management
Test Data Management
What is data masking?
What is data masking?
Data de-identification
Data masking vs data tokenization: differences and use cases
Data masking vs data tokenization: differences and use cases
Data de-identification
What is data obfuscation?
What is data obfuscation?
Data de-identification

Data de-identification

Explore the world of data de-identification—from anonymization to data masking to redaction—and discover how it plays a crucial role in safeguarding sensitive information while maintaining data utility.
See all

What is data de-identification?

Data de-identification

Data anonymization: a guide for developers

Data de-identification

Data anonymization vs data masking: is there a difference?

Data de-identification

What is data masking?

Data de-identification

Static vs dynamic data masking

Data de-identification

Data masking vs data tokenization: differences and use cases

Data de-identification

What is data obfuscation?

Data de-identification

Understanding automated data redaction

Data de-identification

Use cases for de-identified datasets

Data de-identification

Data de-identification in the finance industry

Data de-identification

Data de-identification in the healthcare industry

Data de-identification

Data privacy vs security: understanding the difference

Data de-identification

Data synthesis

Uncover the intricacies of data synthesis and how it empowers organizations to maximize their data for use in software testing and AI development.
See all

Guide to synthetic test data generation

Data synthesis

How to generate synthetic data: a comprehensive guide

Data synthesis

Advanced techniques for generating synthetic test data

Data synthesis

Guide to data privacy compliance for financial institutions

Data synthesis

Test data management

Gain expert insight into test data management, from optimizing software testing workflows to safeguarding sensitive data and ensuring compliance, all while maximizing developer productivity.
See all

Guide to test data management

Test Data Management

The hidden value of test data: a case study on tech debt & business value

Test Data Management

How to gather test data for testing purposes: a guide

Test Data Management

Guide to test data automation

Test Data Management

The importance of using reliable datasets for testing, QA, and development

Test Data Management

Unstructured data management: what it is and how to manage it

Test Data Management

How to overcome common data provisioning challenges

Test Data Management

What is a database on demand?

Test Data Management

The role of Ephemeral environments in QA

Test Data Management

Optimizing Oracle database management, part 1: common challenges & innovative solutions

Test Data Management

Optimizing Oracle database management, part 2: CDB, PDB, & key features

Test Data Management

Optimizing Oracle database management, part 3: benefits & best practices of Ephemeral data environments

Test Data Management

Tonic vs Delphix vs K2View vs IBM Optim. A full comparison.

Test Data Management

7 test data pitfalls in software development

Test Data Management

Data privacy in AI

Understand the requirements, consequences, and implications of using sensitive data in AI workflows, and learn how to optimize your unstructured data to ensure data utility, data privacy, and regulatory compliance.
See all

AI & data privacy: what every organization needs to know

Data privacy in AI

The importance of AI Compliance for your business

Data privacy in AI

Privacy by Design in generative AI: building secure and trustworthy AI systems

Data privacy in AI

Safeguarding data privacy while using LLMs

Data privacy in AI

Understanding data redaction: methods, use cases, and benefits

Data privacy in AI

The role of NER in GDPR compliance and beyond

Data privacy in AI

AI in healthcare: data privacy and ethics concerns

Data privacy in AI

Understanding model memorization in machine learning

Data privacy in AI

Understanding LLM security risks (with solutions)

Data privacy in AI

Best LLM security tools: features & more

Data privacy in AI

AI model training

Explore the latest developments in AI model training, including state-of-the-art techniques, common challenges, and best practices, from sourcing quality training data to optimizing your models with retrieval-augmented generation.
See all

Balancing compliance and data utility in AI model training

AI model training

Understanding named entity recognition (NER) models

AI model training

Quickly building training datasets for NLP applications

AI model training

Synthesizing healthcare data for AI model training, with HIPAA Expert Determination

AI model training

A comprehensive guide to ethical fine-tuning of Large Language Models

AI model training

What is model hallucination?

AI model training

What is retrieval augmented generation? The benefits of implementing RAG in using LLMs

AI model training

RAG chatbot: What it is, benefits, challenges, and how to build one

AI model training

Top 5 trends in enterprise RAG

AI model training

Tonic Structural how-tos

Learn best practices and helpful tips for using Tonic Structural, the test data management platform for developers, in these step-by-step guides.
See all

Creating an enterprise test data strategy with Tonic Structural

Tonic Structural how-tos

Integrating Tonic Structural with your existing tech stack

Tonic Structural how-tos

Ensuring data privacy with privacy rankings in Tonic Structural

Tonic Structural how-tos

Custom sensitivity rules to automate sensitive data detection

Tonic Structural how-tos

Using Tonic Structural and the Safe Harbor method to de-identify PHI

Tonic Structural how-tos

Maintaining data relationships in Structural generation output

Tonic Structural how-tos

Integrating Tonic Structural into your data refresh and CI/CD pipelines

Tonic Structural how-tos

Security for Tonic.ai cloud products

Tonic Structural how-tos

Tonic Textual how-tos

Learn best practices and helpful tips for using Tonic Textual, the unstructured data de-identification and synthesis platform for AI workflows, in these step-by-step guides.
See all

Using custom models in Tonic Textual to redact sensitive values in free-text files

Tonic Textual how-tos

De-identifying your unstructured data in Databricks with Tonic Textual

Tonic Textual how-tos

De-identifying free-text data in Snowflake using Tonic Textual

Tonic Textual how-tos

How to prevent data leakage in your AI applications with Tonic Textual and Snowpark Container Services

Tonic Textual how-tos

How to automatically redact sensitive text data In JSON format

Tonic Textual how-tos

Tonic Ephemeral how-tos

Learn best practices and helpful tips for using Tonic Ephemeral, a solution for spinning up ephemeral databases on demand.
See all

How to create database subsets for Ephemeral environments

Tonic Ephemeral how-tos

All guides

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Data in action: how quality data can revolutionize the financial industry

Developer productivity
Tonic Structural
Tonic Textual
Developer productivity

AI in healthcare: data privacy and ethics concerns

Data privacy in AI
Tonic Structural
Tonic Textual
Data privacy in AI

How to gather test data for testing purposes: a guide

Test Data Management
Tonic Structural
Tonic Ephemeral
Tonic Textual
Test Data Management

Data in action: how quality data can transform the healthcare industry

Developer productivity
Tonic Structural
Tonic Textual
Developer productivity

How data quality issues can slow down product development

Developer productivity
Tonic Structural
Tonic Textual
Tonic Ephemeral
Developer productivity

How better data helps you do more

Developer productivity
Tonic Structural
Tonic Textual
Developer productivity

The importance of using reliable datasets for testing, QA, and development

Test Data Management
Tonic Structural
Tonic Ephemeral
Test Data Management

A comprehensive guide to ethical fine-tuning of Large Language Models

AI model training
Tonic Textual
AI model training

Privacy by Design in generative AI: building secure and trustworthy AI systems

Data privacy in AI
Tonic Textual
Data privacy in AI

How secure, high-quality data can accelerate your time to market

Developer productivity
Tonic Structural
Tonic Textual
Tonic Ephemeral
Developer productivity

Advanced techniques for generating synthetic test data

Data synthesis
Tonic Structural
Tonic Textual
Data synthesis

Creating an enterprise test data strategy with Tonic Structural

Tonic Structural how-tos
Tonic Structural
Tonic Ephemeral
Tonic Structural how-tos

Balancing compliance and data utility in AI model training

AI model training
Tonic Textual
AI model training

Integrating Tonic Structural with your existing tech stack

Tonic Structural how-tos
Tonic Structural
Tonic Structural how-tos

How to overcome common data provisioning challenges

Test Data Management
Tonic Structural
Tonic Ephemeral
Test Data Management

AI & data privacy: what every organization needs to know

Data privacy in AI
Tonic Structural
Tonic Textual
Data privacy in AI

Use cases for de-identified datasets

Data de-identification
Tonic Structural
Data de-identification

Synthesizing healthcare data for AI model training, with HIPAA Expert Determination

AI model training
Tonic Textual
AI model training

Data privacy vs security: understanding the difference

Data de-identification
Tonic Structural
Tonic Textual
Data de-identification

The importance of AI Compliance for your business

Data privacy in AI
Tonic Textual
Data privacy in AI

Unstructured data management: what it is and how to manage it

Test Data Management
Tonic Textual
Test Data Management

RAG chatbot: What it is, benefits, challenges, and how to build one

AI model training
Tonic Textual
AI model training

Best LLM security tools: features & more

Data privacy in AI
Tonic Textual
Data privacy in AI

Understanding LLM security risks (with solutions)

Data privacy in AI
Tonic Textual
Data privacy in AI

Make your sensitive data usable for testing and development.

Unblock data access, turbocharge development, and respect data privacy as a human right.
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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.