Ziyi Song
1995 Turk St, Apt 4, San Francisco, CA 94115, USA.
*Corresponding author: Ziyi Song
Abstract
Conventional approaches to data platform architecture optimization struggle to meet the increasing demands of high concurrency, real-time response, and heterogeneous data environments. As intelligent technologies advance, decision mechanisms centered on model feedback are being embedded into architectural workflows, transforming static infrastructures into adaptive systems. There is a pressing need to define how AI-assisted decision-making integrates with platform structures and to establish generalized implementation pathways. This study identifies key technical foundations for embedding decision intelligence and presents four representative design pathways: intelligent diagnostics, model-driven reconfiguration, algorithmic scheduling, and cross-layer closed-loop control. Practical validation confirms that these pathways significantly enhance both system performance and decision efficiency within operational data environments.
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How to cite this paper
Research on Implementation Pathways of AI-assisted Decision-making in Data Platform Architecture Optimization
How to cite this paper: Ziyi Song. (2025) Research on Implementation Pathways of AI-assisted Decision-making in Data Platform Architecture Optimization. Advances in Computer and Communication, 6(4), 236-243.
DOI: http://dx.doi.org/10.26855/acc.2025.10.014