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What is Sogeti Artificial Data Amplifier (ADA)?

In today's business landscape, data is a vital resource that organizations rely on heavily. By utilizing advanced AI models, companies can create and analyze detailed customer profiles, spot new trends, and explore additional growth opportunities. Nevertheless, the creation of accurate and dependable AI models requires extensive datasets, which brings forth challenges concerning both the quality and the volume of the information gathered. Additionally, stringent regulations like GDPR restrict the handling of certain sensitive data, including that which pertains to customers. This situation necessitates a novel approach, especially in software testing scenarios where acquiring high-quality test data is often challenging. Frequently, businesses turn to actual customer data, which can lead to potential breaches of GDPR and the accompanying threat of hefty penalties. Although experts predict that AI could boost productivity by at least 40%, many companies struggle to implement or fully leverage AI technologies due to these data-related challenges. To overcome these hurdles, ADA harnesses state-of-the-art deep learning methods to create synthetic data, offering a practical alternative for businesses looking to manage the intricacies of data use effectively. This forward-thinking strategy not only reduces compliance risks but also facilitates a smoother and more efficient integration of AI solutions into business operations, ultimately helping companies to thrive in a competitive environment.

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

Integrations Supported

Apache Kafka
GitLab
JSON
Java
JavaScript
Jenkins
XML

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Sogeti

Company Location

France

Company Website

www.sogeti.com/services/artificial-intelligence/artificial-data-amplifier/

Company Facts

Organization Name

Benerator

Company Location

Germany

Company Website

www.benerator.de/

Categories and Features

Categories and Features

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