Construction of Engineering Material Demand Data Space Integrating Macroeconomic Data

Accurate prediction of material demand of engineering projects is helpful to reduce engineering construction costs. The materials demand is not only affected by internal factors, but also by external macro-economy, which mainly affects enterprise investment, planning, and construction. However, the material demand forecasting generally only considers the internal influencing factors, failing to adjust the material procurement plan in time depending on the macroeconomic policies changes. Therefore, this paper takes power engineering projects as an example and constructs a power material demand Data space integrating macroeconomic data, to explore the internal and external factors’ influence on engineering materials demand. Firstly, ETL, Web Crawler, and other data collection technologies are used to collect internal and external macroeconomic data related to the material of power projects. Secondly, the collected data is stored in the data spatial database storage system. Then, the outliers and missing values are processed, and the text data is transformed into numerical data through the BERT model. Finally, the data index method, data association analysis, and evolution modeling of Data space are studied.