A new challenge for data analytics: transposons
| Autor: | Jesús S. Aguilar-Ruiz, Ralf Erik Wellinger |
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| Přispěvatelé: | Universidad de Sevilla. Departamento de Genética |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname idUS. Depósito de Investigación de la Universidad de Sevilla |
| Popis: | The evolution of the Data Analytics field, both in its scientific dimension, i.e. Data Analytics Science (research and development of machine learning techniques), and in its engineering extension, i.e. Data Analytics Engineering (analysis, design, implementation and deployment of Data Analytics projects), has been uneven over the last four decades and, to a large extent, conditioned by the growth rate on the capacity to generate information. The global volume of information reaching the Internet has been steadily increasing, far exceeding linearity over the last decades (currently, global traffic is around 2EB/day). Apart from the recent technological development, which includes the widespread use of mobile devices, the reduction in cost of sensors, or the improved performance of IT infrastructures, all of which have led to massive data generation, we find a reliable picture of how the typology of data has evolved in the datasets that have been used by the scientific community as a basis for the comparative analysis of innovative algorithmic approaches in Data Analytics. |
| Databáze: | OpenAIRE |
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