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What is Tonic?

Tonic offers an automated approach to creating mock data that preserves key characteristics of sensitive datasets, which allows developers, data scientists, and sales teams to work efficiently while maintaining confidentiality. By mimicking your production data, Tonic generates de-identified, realistic, and secure datasets that are ideal for testing scenarios. The data is engineered to mirror your actual production datasets, ensuring that the same narrative can be conveyed during testing. With Tonic, users gain access to safe and practical datasets designed to replicate real-world data on a large scale. This tool not only generates data that looks like production data but also acts in a similar manner, enabling secure sharing across teams, organizations, and international borders. It incorporates features for detecting, obfuscating, and transforming personally identifiable information (PII) and protected health information (PHI). Additionally, Tonic actively protects sensitive data through features like automatic scanning, real-time alerts, de-identification processes, and mathematical guarantees of data privacy. It also provides advanced subsetting options compatible with a variety of database types. Furthermore, Tonic enhances collaboration, compliance, and data workflows while delivering a fully automated experience to boost productivity. With its extensive range of features, Tonic emerges as a vital solution for organizations navigating the complexities of data security and usability, ensuring they can handle sensitive information with confidence. This makes Tonic not just a tool, but a critical component in the modern data management landscape.

What is IBM InfoSphere Optim Data Privacy?

IBM InfoSphere® Optim™ Data Privacy provides an extensive range of tools aimed at effectively concealing sensitive data in non-production environments such as development, testing, quality assurance, and training. This all-in-one solution utilizes a variety of transformation techniques to substitute sensitive information with realistic, functional masked versions, thereby preserving the confidentiality of essential data. Among the masking methods employed are the use of substrings, arithmetic calculations, generation of random or sequential numbers, date manipulation, and the concatenation of data elements. Its sophisticated masking capabilities ensure that the formats remain contextually relevant and closely mimic the original data. Users are empowered to implement a wide selection of masking strategies as needed to protect personally identifiable information and sensitive corporate data across applications, databases, and reports. By leveraging these data masking functionalities, organizations can significantly reduce the risk of data exploitation by obscuring, privatizing, and safeguarding personal information shared in non-production settings, thus improving data security and regulatory compliance. Furthermore, this solution not only addresses privacy concerns but also enables businesses to uphold the reliability of their operational workflows. Through these measures, companies can navigate the complexities of data privacy with greater ease.

Media

Media

Integrations Supported

SQL Server
Amazon Aurora
Amazon Redshift
Apache Spark
Databricks
Google Cloud BigQuery
MongoDB
MySQL
Oracle Database
PostgreSQL
Yellowbrick

Integrations Supported

SQL Server
Amdocs Customer Experience Suite
Hadoop
IBM Cloud
IBM Db2
IBM InfoSphere Optim
IBM Informix
JD Edwards EnterpriseOne
Oracle PeopleSoft
Oracle Siebel CRM

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows
Linux

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Tonic

Date Founded

2018

Company Location

United States

Company Website

www.tonic.ai/

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/il-en/products/infosphere-optim-data-privacy

Categories and Features

Categories and Features

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