Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The increasing risks to security and the rise of stringent privacy laws have necessitated a more cautious approach to handling sensitive information. Oracle Data Masking and Subsetting offers database users a solution to enhance security, streamline compliance efforts, and lower IT expenses by sanitizing production data copies for use in testing, development, and various other functions, while also allowing for the removal of superfluous data. This tool allows for the extraction, obfuscation, and sharing of both full copies and subsets of application data with partners, whether they are within or outside the organization. By doing so, it ensures the database's integrity remains intact, thus supporting the ongoing functionality of applications. Additionally, Application Data Modeling automatically identifies columns within Oracle Database tables that contain sensitive data through established discovery patterns, including national IDs, credit card details, and other forms of personally identifiable information. Furthermore, it can recognize and map parent-child relationships that are defined within the database structure, enhancing the overall data management process.
Description
The Soflab G.A.L.L. application aims to anonymize sensitive information in non-production settings, facilitating the creation of high-quality synthetic data that mirrors real datasets, thus enabling effective testing processes. As it safeguards sensitive details, the application effectively mitigates the risk of data leaks. By substituting genuine data with artificial counterparts, it reduces the potential for data breaches while identifying sensitive or erroneous entries. This results in decreased legal and financial risks while ensuring the protection of customer transactional data. The application promotes a unified approach to anonymization across various non-production systems, thus maintaining a consistent data model and preserving connections with production data. Additionally, synthetic data generated from essential production attributes retains statistical integrity for business intelligence and artificial intelligence applications. A centralized test data repository allows for controlled data reuse, which not only lowers maintenance expenses and accelerates deployment timelines—up to five days—but also facilitates simulation and reusable scenarios effectively. Overall, the application enhances testing efficiency while prioritizing data security.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
IBM Db2
Yes
IBM Informix
Yes
MySQL
Yes
Oracle Database
Yes
Oracle E-Business Suite
Yes
SQL Server
Yes
Integrations
IBM Db2
No
IBM Informix
No
MySQL
No
Oracle Database
No
Oracle E-Business Suite
No
SQL Server
No
Pricing Details
$230 one-time payment
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/database/technologies/security/data-masking-subsetting.html
Vendor Details
Company Name
Soflab Technology Sp. z o.o.
Founded
2008
Country
Poland
Website
soflab.pl/en/