British DataOps platform provider Synthesized Ltd. said today it’s partnering with the data protection firm BigID Inc. on a new offering that enables users to generate, mask, subset and then repopulate sensitive data, without risking that some of the information might go missing.

Synthesized is the creator of a DataOps platform that’s designed to help fast track artificial intelligence model development and training. DataOps refers to a collaborative data management practice aimed at improving the communication, integration and automation of data flows between data managers and data consumers across an organization.

The company’s tools make it easy for enterprises to work with highly sensitive data in a very secure fashion. To do this, it creates “synthetic data” that looks and behaves exactly like the original dataset. However, this synthetic data is made up entirely of synthesized data points, ensuring AI models can be trained accurately using sensitive data as the base — albeit not for the actual training.

As for BigID, it’s a provider of software that companies can use to secure customer data in a way that satisfies privacy regulations. BigID relies on advanced machine learning and an innovation it terms “identity intelligence” to enable users to find, track and “de-risk” identity data that’s stored on computer servers. It does this by automatically cataloging and mapping sensitive information across an entire data environment, incorporating active metadata and classification.

Given that they operate in adjacent fields, it’s no surprise to learn that Synthesized and BigID believe their mutual offerings can work hand in hand, and that’s the thrust of today’s announcement. Synthesized said that by partnering with BigID, joint customers will be able to automate the de-identification of sensitive data, a task that’s normally done manually while taking up significant resources.

De-identification of data is a common process applied to datasets that aims to eliminate privacy risks to individuals, protected groups, and establishments. In this way, companies can then analyze sensitive data for insights, or use it to train AI models.

Synthesized said partnering with BIgID allows it to de-identify sensitive data based on its level of sensitivity, increasing time to value by enabling access to compliant test data in a matter of minutes. At the same time, working with BigID removes the manual effort involved in test data generation, while enabling this data to be moved to the cloud quickly and safely, in a compliant way.

According to Synthesized, there’s a big demand for this kind of speed. The company explains in a recent blog post that increased data privacy requirements in many parts of the world mean it can take anywhere from four to 20 weeks to safely and compliantly access sensitive information. The problem for larger organizations is that the data they need is often siloed across multiple countries, complicating efforts at collaboration.

Synthesized Chief Executive Nicolai Baldin said the partnership means application development and quality assurance teams can now create the “highest quality” synthetic data and leverage their most sensitive data assets in minutes..

“BigID finds, classifies and catalogs all of your sensitive data,” said BigID Field Chief Technology Officer Christopher Glover. “The integration with Synthesized allows customers to quickly de-identify sensitive data through the generation of safe and compliant, high-quality synthetic test data for use in non-production environments.”

Image: Synthesized