Learn how to make your sensitive data usable in software and AI development through our comprehensive guides.
What is Retrieval Augmented Generation? The benefits of implementing RAG in using LLMs
Data privacy in AI
The hidden value of test data: a case study on tech debt & business value
Test Data Management
Data de-identification in the healthcare industry
Data de-identification
Data anonymization vs data masking: is there a difference?
Data de-identification
Static vs dynamic data masking
Data de-identification
De-identifying your unstructured data in Databricks with Tonic Textual
Tonic Textual how-tos
Data anonymization: a guide for developers
Data de-identification
Quickly building training datasets for NLP applications
Data privacy in AI
How to generate synthetic data: a comprehensive guide
Data synthesis
Data de-identification in the finance industry
Data de-identification
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
Test Data Management
Optimizing Oracle database management, part 2: CDB, PDB, & key features
Test Data Management
Optimizing Oracle database management, part 1: Common challenges & innovative solutions
Test Data Management
Ensuring data privacy with Privacy Rankings in Tonic Structural
Tonic Structural how-tos
The Role of Ephemeral Environments in QA
Test Data Management
Guide to data privacy compliance for financial institutions
Data synthesis
Understanding automated data redaction
Data de-identification
The Role of NER in GDPR Compliance and Beyond
Data privacy in AI
Security for Tonic.ai cloud products
Tonic Structural how-tos
Top 5 trends in enterprise RAG
Data privacy in AI
What is model hallucination?
Data privacy in AI
What is a database on demand?
Test Data Management
Understanding Named Entity Recognition (NER) models
Data privacy in AI
Safeguarding data privacy while using LLMs
Data privacy in AI
What is data de-identification?
Data de-identification
How to create database subsets for ephemeral environments
Tonic Ephemeral how-tos
Understanding Model Memorization in Machine Learning
Data privacy in AI
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
7 Test Data Pitfalls in Software Development
Test Data Management
Guide to test data automation
Test Data Management
Guide to synthetic test data generation
Data synthesis
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
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.
Test Data Management
Using custom models in Tonic Textual to redact sensitive values in free-text files
Tonic Textual how-tos
What is data obfuscation?
Data de-identification
Data masking vs data tokenization: differences and use cases
Data de-identification
What is Data Masking?
Data de-identification
Guide to Test Data Management
Test Data Management
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.
How to generate synthetic data: a comprehensive guide
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.
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
The hidden value of test data: a case study on tech debt & business value
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.
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.