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Evaluating a Decentralized Data Sharing Platform for Global Telecoms Association

Techniques:

Generative ai

Client Website:

Objectives

To evaluate the suitability of a decentralised platform to enable members of an association to share their data in a safe and secure way

Problem

We recently worked with a global association of mobile operators that drives innovation and societal impact. They engaged us to provide a technical and structured evaluation of a decentralized data-sharing platform in development from a third party company, that they desire to offer to their clients. We cooperated with the development company to gain a deep understanding of it and then provided the necessary feedback to align with the client’s needs. The goal for us was to assess the platform and determine whether it was meeting the demands of the telecom member organisations, which will be the final users of the platform, enabling them to securely and efficiently share data with each other while maintaining control over access and privacy.

Solution

We collaborated with the client to evaluate the data-sharing platform on critical criteria like data privacy and security, scalability, interoperability, data quality and management, user experience, and performance. We tested its infrastructure, provided feedback to the development team, and produced a detailed report of the analyses conducted.

The platform has a decentralized architecture that keeps data under the control of the organisation that owns it, exposing only the metadata of the shared files for authorised access. Users can create secure data-sharing groups and set up role-based access to specific datasets. While the user experience was intuitive and performance is efficient, data management and quality had some space for improvement. This was openly discussed with the development team to ensure alignment with the client’s needs. Our suggestions for better data and metadata validation and improved findability were added to the platform’s development roadmap.

We also tested real-world use cases provided by the client, including extracting quantitative data from PDFs shared via the platform and developing a natural language querying system using Retrieval Augmented Generation. These use cases demonstrated the potential of the data-sharing solution in handling complex data retrieval and its future applications that user organisations can make use of.

Impact

The evaluation demonstrated the potential uses of a well developed decentralised data-sharing solution for the client and its member organisations. The platform’s ability to manage data securely through metadata-driven access allows organisations to maintain control over their data while participating in a larger data-sharing ecosystem. This has potential gains for the organisations through the creation of interesting insights, improvements in efficiency and created value.

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