What Problems Does a Distributed Data Ecosystem Solve?

Data is an important aspect of society. Good data transformed into useful information can help unlock opportunities for people. Unfortunately, many regions of the world are not continuously connected with quality broadband. Even in better connected places, accessing good data can be a problem. “No data” to us means little, fragmented, low quality, low fidelity, and/or unavailable/inaccessible data. A distributed data ecosystem (DDE) can change that.


What is a DDE?

A distributed data ecosystem includes physical infrastructure, digital data and analytics infrastructure, and people infrastructure. The physical infrastructure operates as a self-contained data ecosystem where connectivity to the Internet is not available or is inadequate; as hybrid infrastructure for asynchronous/on-off environments including mobile transport; and as a fully connected infrastructure to the global Internet in more connected places like cities. The digital data and analytics infrastructure provides robust operations to generate/collect, ingest, manage, analyze, use, disseminate, and store data in a distributed or self-contained environment. The people infrastructure develops and deploys teams and stakeholders to manage the majority of the operation locally, according to global best practices and standards. The result is robust data capabilities in geographic regions, such as Africa, where it is difficult to get reliable, quality data. The platform reduces information asymmetry for institutions, investors, and governments; increase the variety and robustness of data available; reduces time windows; and increases reliability and quality of data for data-driven applications, platforms, decisions, and actions.


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