Constructing Solution: Analyzing Challenges in the Construction Industry using data Science Techniques.

Abstract

The construction industry, a critical sector in global economic development, faces numerous challenges that affect productivity, safety, timelines, and budget control. Issues such as inefficient resource allocation, unforeseen delays, cost overruns, safety hazards, and inadequate communication contribute to the inefficiencies. With the advent of data science and machine learning techniques, a new paradigm can be developed to analyze and mitigate these challenges. This paper presents a framework that applies data science methods to recognize and tackle the key challenges in the construction sector. By using predictive analytics, data mining, and machine learning, the proposed system identifies potential issues before they occur, enabling stakeholders to make informed decisions. The research discusses the design, development, and implementation of this data-driven framework aimed at improving project outcomes and optimizing resource management in construction projects.