Authors:
Spyros Loizou
;
Michalis Pingos
and
Andreas Andreou
Affiliation:
Department of Computer Engineering and Informatics, Cyprus University of Technology, Limassol, Cyprus
Keyword(s):
Digital Twins, Data Lakes, Data Blueprints, Graphical Dashboard, Smart Data Processing, Big Data Characteristics.
Abstract:
Advanced analytical techniques and sophisticated decision-making strategies are imperative for handling extensive volumes of data. As the quantity, diversity, and speed of data increase, there is a growing lack of confidence in the analytics process and resulting decisions. Despite recent advancements, such as metadata mechanisms in Big Data Processing and Systems of Deep Insight, effectively managing the vast and varied data from diverse sources remains a complex and unresolved challenge. Aiming to enhance interaction with Data Lakes, this paper introduces a framework based on a specialized semantic enrichment mechanism centred around data blueprints. The proposed framework takes into account unique characteristics of the data, guiding the process of locating sources and retrieving data from Data Lakes. More importantly, it facilitates end-user interaction without the need for programming skills or database management techniques. This is performed using Digital Twin functionality wh
ich offers model-based simulations and data-driven decision support.
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