Scalable Data Processing Pipelines: The Role of AI and Cloud Computing
Abstract
The rapid growth of data in modern enterprises necessitates the development of scalable and efficient data processing pipelines. Artificial Intelligence (AI) and cloud computing have emerged as transformative technologies to address the challenges associated with data volume, velocity, and variety. This paper explores the integration of AI-driven automation and analytics with cloud-based infrastructure to design scalable data pipelines that support real-time processing and decision-making. Key components, including data ingestion, transformation, storage, and retrieval, are examined in the context of their scalability and optimization through AI and cloud technologies. The study highlights the benefits of this integration, such as reduced latency, enhanced resource allocation, and cost-efficiency, while addressing potential challenges like data security and compliance. Case studies demonstrate the practical implementation of these pipelines, offering quantitative results that underline their effectiveness in handling large-scale enterprise workloads
References
Kim, S., & Adams, Q. M. (2018). Fintech Disruption: AI Innovations in Emerging Market Banking. Journal of Financial Technology, 7(2), 145-162.
Wang, L., & Zhang, Y. (2019). Operational Efficiency and AI Integration: An Empirical Study. Journal of Financial Automation, 15(1), 32-50.
Klein, R., et al. (2020). Revolutionizing Customer Interactions: The AI Advantage. International Journal of Human-Computer Interaction, 18(4), 201-220.
Martinez, C. R., & Wang, Q. (2017). Ethical Considerations in AI-Driven Banking. Journal of Business Ethics, 25(2), 89-106.
Kim, S., & Jones, M. B. (2019). The Role of Explainable AI in Financial Decision-making. Journal of Cognitive Computing, 14(2), 78-94.
Harris, E. L., et al. (2018). Longitudinal Impact Assessment of AI in Emerging Market Banking. Journal of Longitudinal Research, 15(4), 201-218.
Dr. A. Saravana Kumar Dr. Prasad Mettikolla.(2014). IN VITRO ANTIOXIDANT ACTIVITY ASSESSMENT OF CAPPARIS ZEYLANICA FLOWERS. International Journal of Phytopharmacology, 5(6), 496-501.
Dr. R. Gandhimathi Dr. Prasad Mettikolla.(2015). EVALUATION OF ANTINOCICEPTIVE EFFECTS OF MELIA AZEDARACH LEAVES. International Journal of Pharmacy, 5(2), 104-108.
G. Sangeetha Dr. Prasad Mettikolla.(2016). ASSESSMENT OF IN VITRO ANTI-DIABETIC PROPERTIES OF CATUNAREGAM SPINOSA EXTRACTS. International Journal of Pharmacy Practice & Drug Research, 6(2), 76-81.
Mettikolla, P., & Umasankar, K. (2019). Epidemiological analysis of extended-spectrum β-lactamase-producing uropathogenic bacteria. International Journal of Novel Trends in Pharmaceutical Sciences, 9(4), 75-82.