All government, business, and non-profit organisations collect voluminous amounts of metadata and data. Traditional techniques struggle to make sense of this overabundance of data, lack of metadata and its context.
This situation contrasts with that prevailing some years ago, when a lack of data was a key concern for decision-makers.
Additional challenges faced now by many data-rich organisations are that data is industry-specific, of variable quality, is not discoverable or connected, and also lacks context. As a result, most data cannot be reliably used or shared.
Enterprises need to manage data responsibly and ethically, but they also want to look for ways to increase its usefulness, its return on investment, and its effectiveness for evidence-based decision-making.
Additionally, enterprises seek minimisation of human intervention in data management, whilst increasing the quality of the metadata, data, and their context, via machine learning (ML) and through human-in-the-loop processes.
Improving metadata and data
SURROUND’s mission is to intelligently discover, connect, and reason about organisational knowledge assets to provide the backbone for informed and contextually-aware strategic and operational decisions.