Unlocking the potential of artificial intelligence for big data analytics

¹ Kazan State Power Engineering University, Kazan, Russia
² Kazan National Research Technical University named after A. N. Tupolev – KAI, Kazan, Russia
³ Limited Liability Company "Complex Infosystems", Kazan, Russia

^* Corresponding author: zarim@rambler.ru

Abstract

This article comprehensively examines the use of artificial intelligence (AI) in big data analytics. It focuses on machine learning and deep learning methods that are leveraged to develop innovative algorithms and solutions across domains like finance, healthcare, environment, and education. The article discusses the benefits of applying AI to big data analysis such as improved efficiency and accuracy of predictions, as well as optimization of decisions. However, it also highlights downsides and challenges such as information processing and security, privacy concerns, and ethical considerations. The opportunities and technological challenges associated with processing huge volumes of data are elaborated. The need for an interdisciplinary approach and importance of proper implementation of AI across various spheres of activity is emphasized to maximize impact on societal and economic advancement. Specifically, the article delves into cutting-edge AI and machine learning techniques that enable identifying complex patterns and extracting meaningful insights from massive, heterogeneous data sources. Real-world case studies demonstrate applied AI transforming decision-making in areas like personalized medicine, predictive maintenance, demand forecasting, and more. The piece highlights best practices and cautions around data quality, algorithmic transparency, model interpretability, and ethical AI to tap the potential of big data analytics while mitigating risks like biases and breaches. It underscores the need for holistic solutions blending AI, domain expertise, and purposeful data science. Overall, the article provides a balanced perspective on modern AI amid the big data revolution. It informs technical and non-technical readers about prospering at the intersection of big data and AI – by being realistic about the challenges, following principles for responsible AI, and focusing on human-centered design.