TEADAL will enable the creation of trusted, verifiable, and energy-efficient data flows, both inside a data lake and across federated data lakes, based on a shared approach for defining, enforcing, and tracking data governance requirements with specific emphasis on privacy/confidentiality. The proposed stretched data lake, i.e. deployed in the continuum, will be based on an innovative control plane able to exploit all the controlled/owned resources across clouds and at the edge to improve data analysis. The resulting capabilities of stretched data lakes also provide the essential basis for creating trustworthy mediatorless federations of data lakes to foster an effective data exchange among organizations while preserving privacy and confidentiality constraints without any imposed, and often not acceptable, third-party coordinator. Finally, applying to the data governance the principles of circular economy, i.e. to reuse data, application, and computation resources belonging to the data lake federation, will enable the creation of platforms for more sustainable data analytics.
The proposed solution aims to lower the effort required for efficient energy and data analysis with privacy- and confidentiality-by-design data management, thus reducing the barriers to sharing and using data among organizations to provide timely and reliable informed decisions. TEADAL will be beneficial for data lake providers, which can exploit additional functions in terms of definition, enforcement, and tracking of privacy- /confidentiality-based policies, as well as business analysts and data scientists which can make full use of data coming from several organizations without implementing complex systems to ensure privacy/confidentiality requirements.
