Evaluation and Dynamic Optimization of Big Data Technology in Engineering Project Resource Allocation

This paper focuses on the innovative application of big data technology in the field of engineering project resource allocation, deeply analyzing its core functional mechanisms in resource evaluation and dynamic optimization. By constructing an evaluation index system for resource allocation that integrates multi-source data, and combining data mining, machine learning, and deep learning algorithms, an intelligent dynamic optimization model for resource allocation is established. Taking a super-high-rise commercial complex construction project as a typical case, this paper details the full-process practice of big data technology from data collection and analysis to optimization decision-making, and quantitatively analyzes its significant effects in improving resource utilization efficiency, reducing project costs, and ensuring construction progress. The study shows that big data technology can provide scientific and precise decision-making basis for engineering project resource allocation, strongly promote the transformation of engineering project management towards intelligence and refinement, and provide new technical paths and practical references for industry development.