Description: Federated data management is an approach that allows the administration and sharing of data between different organizations while ensuring data sovereignty. This system is based on the idea that entities can collaborate and share information without relinquishing control over their own data. In a Zero Trust cloud environment, federated data management becomes an essential component as it promotes security and privacy by allowing data to remain in its original location while facilitating access and use of this data by other organizations. The main features of this approach include interoperability, data security, and the ability to comply with privacy regulations. Federated data management optimizes collaboration between organizations and minimizes the risks associated with data transfer, which is crucial in a world where cyber threats are becoming increasingly sophisticated. In summary, this system represents an innovative solution for data management in a Zero Trust environment, allowing organizations to work together securely and efficiently.
History: Federated data management has evolved over the past two decades, driven by the need for inter-organizational collaboration and the rise of data privacy regulations. Although the concept of data federation dates back to early distributed database systems in the 1990s, its application in cloud environments and Zero Trust settings has gained relevance in the last decade, especially with the rise of digital transformation and the adoption of cloud solutions.
Uses: Federated data management is primarily used in sectors where collaboration between organizations is essential, such as healthcare, education, and finance. It enables institutions to share data for analysis and studies without compromising individual data privacy. Additionally, it is applied in compliance with data protection regulations, where organizations must demonstrate that they handle information responsibly and securely.
Examples: An example of federated data management is the use of research platforms that allow different hospitals and research centers to share patient data for clinical studies without transferring the data to a single repository. Another example is the use of data management systems in the finance sector, where multiple institutions collaborate on fraud detection by sharing information without losing control over their own data.
