Enterprise Data Sharing — Under the Hood

Read Time 2 mins | Written by: Intlabs team

Server Rack - Photo by Taylor Vick on Unsplash

“Technologies to help share, process, analyze and optimize the data pipeline, including those that can assist with the real-time analysis of relevant data are critical.”

— Mike Anderson, CTO at Intlabs.io

Enterprise organizations are changing the way they manage their data.

But efficiency is the least of their worries, considering the significant challenges faced by organizations managing large volumes of sensitive data. Procurement and data analysts are requesting more intelligent software solutions that not only optimizes their processes but mitigates risk by design, from the protection of streaming data from theft, tampering and eavesdropping, to providing immutable auditing and additional insights, such as geospatial mapping, for deeper intelligence, surveillance, tracking and analysis. More than ever, enterprise organizations are viewing data as a strategic asset. To address ever-evolving requirements, the team at Intlabs developed ORIGIN. 


ORIGIN is based on the concept of a data pipeline, as well as being designed to address the ever-evolving requirements of data analysts and intelligence experts as data usage and transfer becomes more nuanced, and privacy regulations adapt to these changes.

"Inside ORIGIN, we created a lightweight data registry that enables the user to define various data sources — internal and external to your organization — as well as the credentials required to access those data sources,” says Mike. Find the rest of his high-level overview of ORIGIN’s capabilities here:

Demo on Youtube

The future of data sharing

Tools like ORIGIN are the answer to the pressing concerns around data governance, risk, and compliance. It provides a sound barrier between data sources and operational users and acts as an access control and delivery mechanism. By employing a decentralized data pipeline architecture, the platform is optimally designed to enable clients to abide by data sovereignty laws and to maintain differential privacy and zero trust principles. This is what the future of enterprise data management looks like.