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What is Soflab G.A.L.L.?

The Soflab G.A.L.L. application is designed to anonymize sensitive information in non-production environments, making it easier to generate high-quality synthetic data that closely resembles actual datasets, which in turn streamlines testing processes. By protecting sensitive information, this application significantly reduces the risk of data leaks. It accomplishes this by replacing real data with artificial alternatives, thereby lowering the chances of data breaches and allowing for the identification of sensitive or incorrect entries. This leads to a reduction in both legal and financial liabilities while ensuring that customer transaction data remains secure. Furthermore, the application advocates for a cohesive approach to anonymization across different non-production systems, which helps maintain a consistent data model and ensures connections with production data are intact. Moreover, the synthetic data derived from key production attributes preserves the statistical integrity necessary for business intelligence and artificial intelligence applications. A centralized repository for test data enables controlled reuse, which not only cuts maintenance costs and speeds up deployment timelines—by as much as five days—but also supports effective simulation and the creation of reusable scenarios. In summary, the application not only enhances testing efficiency and prioritizes data security but also fosters innovation in data management practices. Consequently, organizations can confidently conduct their testing without the fear of compromising sensitive information.

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.

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Integrations Supported

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

Integrations Supported

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

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard 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
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Soflab Technology Sp. z o.o.

Date Founded

2008

Company Location

Poland

Company Website

soflab.pl/en/

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

Data Privacy Management

Access Control
CCPA Compliance
Consent Management
Data Mapping
GDPR Compliance
Incident Management
PIA / DPIA
Policy Management
Risk Management
Sensitive Data Identification

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