TEADAL

The TEADAL project aims to provide core technologies for creating stretched data lakes spanning the continuum and multi-cloud, providing privacy, confidentiality, and energy-efficient data management.

The TEADAL data lake technologies will enable trusted, verifiable and energy-efficient data flows in a stretched data lake and across a trustworthy mediator-less federation. Data analytics is one of the main cornerstones in many enterprise architectures. The data lake paradigm is increasingly adopted to assist organisations in making reliable, accurate, and fast decisions. Although the initial approaches to address these issues saw the data lakes as the evolution of data warehouses to be implemented on-premises, cloud providers are nowadays including in their offerings platforms able to set up and run them.

Nevertheless, the increasing amount of data generated at the edge and the need to enable data sharing among organisations are posing new challenges in terms of performance, energy efficiency, and privacy/confidentiality, which can be properly addressed with data lakes which are deployed along the whole computing continuum as well as building a federation of such data lakes.

Project objectives:

• Build efficient data lakes solutions with ease data handling across the computing continuum

TEADAL demonstrates a data lake control plane that handles the non-functional aspects of workloads across the computing continuum – automatically optimizes performance, enforces policies, run transformations, and secure the data paths, independently of the user code.

• Construct trustworthy data lakes and mediatorless federation of data lakes

The TEADAL project enables the creation of trustworthy data lakes where privacy/confidentiality requirements are satisfied when handling data along the continuum as well as then shared among organizations.

• Reduce the environmental impact of data analytics through energy-efficient federation of stretched data lakes

The TEADAL project aims to apply the principle of circular economy to the involved data (e.g., reducing data duplication, balancing data reuse and data accuracy, reduce the data movement) considering both design and operational levels.

• Build privacy, organisational policies and GDPR compliant federation of stretched data lakes

The TEADAL project proposes a shared knowledge on the exact semantic of privacy/confidentiality requirements and how they are enforced, to avoid erroneous (different) interpretations that will lead to a break of the trust established between the federated data lakes.

• Contribute to and influence European research and initiatives with an aim to improve data sharing

The TEADAL project aims to gather feedback, explore problems beyond the ones identified by partners, and to provide to such stakeholders concrete demonstrator of key innovations that the project will develop and to disseminate the resulting innovative approaches to improve trustworthy data sharing in Europe.

This project has received funding from the EU’s Horizon Europe Programme under grant agreement no 101070186