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The Impact of Artificial Intelligence on Big Data Analysis and Digital Transformation
Subject area: Science,Engineering and Technology · Area of research: Technology
Abstract
Big Data analysis, driven by Artificial Intelligence (AI), has become essential for digital transformation across various sectors. The increasing volume of generated data demands powerful tools like AI to process, interpret, and extract valuable insights. Companies of all sizes have adopted AI to optimize operations, personalize products, and improve customer experience. Machine learning algorithms and neural networks are used to identify patterns and trends in large datasets, a task impossible to achieve manually. In the e-commerce sector, AI predicts purchasing behaviors and personalizes recommendations. In biotechnology and climate science, it facilitates essential discoveries, such as new treatments and solutions. Additionally, AI has transformed healthcare through personalized medicine and helped predict demand and perform predictive maintenance in industries like manufacturing and energy. Real-time data processing, offered by AI, is a strategic advantage in areas like the financial market, where rapid decision-making is crucial. Despite advancements, ethics, privacy, and algorithm transparency are challenges that must be addressed. The collection and use of personal data require rigorous security and transparent practices. The integration of AI and Big Data is transforming business decision-making, making it more data-driven and insight-based. However, this revolution also requires ethical reflection, particularly regarding the use of sensitive data and corporate responsibility. The future of AI and Big Data demands a balanced approach, with technological innovation and ethical commitment, to maximize its social and economic benefits.
Keywords
Big Data, Artificial Intelligence, Digital Transformation, Algorithms, Ethics.
How to cite this paper
@article{1707393,
author = {Rafael Carvalho Turatti},
title = {The Impact of Artificial Intelligence on Big Data Analysis and Digital Transformation},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {9},
pages = {253-257},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1707393.pdf},
abstract = {Big Data analysis, driven by Artificial Intelligence (AI), has become essential for digital transformation across various sectors. The increasing volume of generated data demands powerful tools like AI to process, interpret, and extract valuable insights. Companies of all sizes have adopted AI to optimize operations, personalize products, and improve customer experience. Machine learning algorithms and neural networks are used to identify patterns and trends in large datasets, a task impossible to achieve manually. In the e-commerce sector, AI predicts purchasing behaviors and personalizes recommendations. In biotechnology and climate science, it facilitates essential discoveries, such as new treatments and solutions. Additionally, AI has transformed healthcare through personalized medicine and helped predict demand and perform predictive maintenance in industries like manufacturing and energy. Real-time data processing, offered by AI, is a strategic advantage in areas like the financial market, where rapid decision-making is crucial. Despite advancements, ethics, privacy, and algorithm transparency are challenges that must be addressed. The collection and use of personal data require rigorous security and transparent practices. The integration of AI and Big Data is transforming business decision-making, making it more data-driven and insight-based. However, this revolution also requires ethical reflection, particularly regarding the use of sensitive data and corporate responsibility. The future of AI and Big Data demands a balanced approach, with technological innovation and ethical commitment, to maximize its social and economic benefits.},
keywords = {Big Data, Artificial Intelligence, Digital Transformation, Algorithms, Ethics.},
month = {March},
}