Analyzing Data Reduction Techniques: An Experimental Perspective

Author:

Fernandes Vítor1,Carvalho Gonçalo2ORCID,Pereira Vasco2ORCID,Bernardino Jorge12ORCID

Affiliation:

1. Coimbra Institute of Engineering, Polytechnic University of Coimbra, Rua Pedro Nunes, Quinta da Nora, 3030-199 Coimbra, Portugal

2. Department of Informatics Engineering, Centre for Informatics and Systems, University of Coimbra, Pólo II, Pinhal de Marrocos, 3030-290 Coimbra, Portugal

Abstract

The exponential growth in data generation has become a ubiquitous phenomenon in today’s rapidly growing digital technology. Technological advances and the number of connected devices are the main drivers of this expansion. However, the exponential growth of data presents challenges across different architectures, particularly in terms of inefficient energy consumption, suboptimal bandwidth utilization, and the rapid increase in data stored in cloud environments. Therefore, data reduction techniques are crucial to reduce the amount of data transferred and stored. This paper provides a comprehensive review of various data reduction techniques and introduces a taxonomy to classify these methods based on the type of data loss. The experiments conducted in this study include distinct data types, assessing the performance and applicability of these techniques across different datasets.

Publisher

MDPI AG

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