Journal of Engineering Research

Big data analysis is of great significance in the schedule prediction and risk management of power grid projects. By analyzing and modeling a large amount of data, it can predict the progress of power grid projects and help project managers make accurate decisions. At the same time, big data analytics can also help identify and manage risks in a project, and take steps to avoid or mitigate the impact of risks in advance. In terms of schedule prediction, big data analysis can establish a model to predict the progress of a project by analyzing historical project data, schedule plans and actual progress. Through comprehensive consideration of multiple factors, such as resource allocation, engineering progress, staffing, etc., accurate project schedule prediction can be provided to help project managers timely adjust resources and schedule plans to ensure the timely completion of the project. In terms of risk management, big data analysis can identify potential risks in a project through the analysis of project-related data. By analyzing historical project data and related influencing factors, risk models can be built to predict, evaluate and quantify the risks that a project may face. Through the identification and evaluation of risks, corresponding risk response strategies can be formulated and timely measures taken to reduce the impact of risks, so as to ensure the smooth progress of the project.

Big data analysis; Power grid projects; Progress prediction; Risk management