Guardat en:
| Autor principal: | |
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| Format: | Recurso digital |
| Idioma: | anglès |
| Publicat: |
Zenodo
2025
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| Matèries: | |
| Accés en línia: | https://doi.org/10.5281/zenodo.14936895 |
| Etiquetes: |
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Taula de continguts:
- <p><em><span>Big Data refers to the extensive and complex datasets generated at unprecedented volumes, velocities, and varieties, which exceed the processing capacity of traditional data management tools. These datasets pose challenges in terms of capturing, storing, transferring, querying, and processing information efficiently and in real-time. To address these challenges, advanced analytics techniques have emerged, often integrating Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) methodologies. The synergy between Big Data and AI has enabled significant advancements, transforming industries such as healthcare, finance, transportation, and education by enabling predictive analytics, real-time decision-making, and personalized solutions. This paper investigates the multifaceted impact of Big Data on AI, focusing on how the availability of large-scale,<span> </span>diverse datasets has enhanced the performance of AI models, driven innovation in algorithm development, and enabled breakthroughs in automation and intelligent systems.<span> </span>Furthermore, the paper highlights the challenges associated with integrating Big Data and AI, including ethical considerations, data privacy, and the need for scalable infrastructure.</span></em></p>