Water Conservancy Data Acquisition and Big Data Service Based on Multi-data Sources

Abstract

To reflect the application value of data development, based on the data of multiple data sources, the water conservancy and the big data service were studied. First, the acquisition of public data was studied. Computers were used to quickly and efficiently collect data into libraries, which greatly reduce the difficulty of data acquisition. Then, the method of data cleaning was determined to improve data quality and enhance the effectiveness and reliability of the data in the application process. Finally, the water conservancy prediction model was applied to the flood prevention decision-making service system based on the integrated platform. The results showed that the acquisition of public data greatly improved the efficiency of data acquisition. By cleaning the obtained data of repeated values, error values, outliers and missing values, higher quality water situation data was obtained. The water conservancy prediction model improved the accuracy of the prediction, and the flood control decision service system provided an efficient and operational integrated platform. Therefore, the water conservancy prediction model has a certain guiding role in flood control decision-making. It is the key to big data services for water conservancy.