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What is Oracle Data Masking and Subsetting?

In response to escalating security threats and the implementation of strict privacy regulations, a more vigilant strategy for managing sensitive information has become essential. Oracle Data Masking and Subsetting provides database professionals with a robust solution that not only fortifies security but also simplifies compliance measures and reduces IT costs by sanitizing copies of production data for various applications, including testing and development, while also enabling the elimination of unnecessary data. This innovative tool facilitates the extraction, obfuscation, and sharing of comprehensive and selective data sets with partners, regardless of whether they are internal or external to the organization, thereby maintaining the integrity of the database and ensuring that applications function smoothly. Furthermore, Application Data Modeling plays a crucial role by automatically detecting columns in Oracle Database tables that hold sensitive information using predefined discovery patterns, such as national IDs and credit card numbers, which are critical for protecting personal information. In addition, it is capable of identifying and mapping parent-child relationships structured within the database, significantly improving the efficacy of data management practices. Overall, these features enhance the organization’s ability to safeguard sensitive data while facilitating better data governance.

What is Benerator?

Conceptually outline your data model using XML, ensuring that business personnel are actively engaged, so that no programming knowledge is necessary. Incorporate a variety of function libraries to create realistic data simulations and develop custom extensions in JavaScript or Java as required. Integrate your data workflows smoothly with tools like GitLab CI or Jenkins while utilizing Benerator’s model-driven data toolkit for generating, anonymizing, and migrating data effectively. Create straightforward XML procedures for anonymizing or pseudonymizing data that are easy for non-developers to understand, all while complying with GDPR regulations to protect customer privacy. Employ methods to mask and obfuscate sensitive information for purposes such as business intelligence, testing, development, or training environments. Collect and integrate data from various sources without compromising its integrity, and support the migration and transformation of data within complex system landscapes. Reapply your data testing models to facilitate the migration of production systems, ensuring that the data remains reliable and consistent within a microservices architecture. Furthermore, it would be beneficial to develop comprehensive user-friendly documentation that aids business users in grasping the data processes involved, thereby enhancing collaboration and understanding across teams. This approach not only fosters a transparent workflow but also strengthens the overall data governance framework within the organization.

Media

Media

Integrations Supported

IBM Db2
IBM Informix
MySQL
Oracle Database
Oracle E-Business Suite
SQL Server

Integrations Supported

Apache Kafka
GitLab
JSON
Java
JavaScript
Jenkins
XML

API Availability

API Availability

Has API

Pricing Information

$230 one-time payment

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/database/technologies/security/data-masking-subsetting.html

Company Facts

Organization Name

Benerator

Company Location

Germany

Company Website

www.benerator.de/

Categories and Features

Data Masking

Not specified

Database Security

Not specified

Categories and Features

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