LI Hao, YANG Jie
Beijing Research Institute of Smart Water Beijing 100036 China
Objectives
Multi source data has multidimensional characteristics, that is, data extracted from different perspectives on the same object, such as content theme dimension, type dimension, structural dimension, time dimension, spatial dimension, etc As a business application display system, the replenishment scheduling app needs to organically integrate multi source data, select the most suitable data source based on the current business scenario, and ensure its timeliness and accuracy To achieve multi source heterogeneous aggregation and full lifecycle monitoring of replenishment data, we can explore the implementation of unified data aggregation and management for replenishment systems based on multi source data fusion technology, timestamp algorithms, and replenishment business logic architecture.
Conclusions
(1) The multi source data fusion and dynamic monitoring technology proposed in this study can effectively solve the problems of association fusion and information supervision of various types of data. This technological achievement can not only assist in the aggregation management of water replenishment scheduling data, but also be applied to various water business data aggregation scenarios based on business work needs, promoting the interconnection and interconnection of water data. (2) It is recommended to strengthen the refined monitoring of each data item in the dataset in various data monitoring scenarios, which can significantly improve data assurance efficiency, save operation and maintenance costs, and ensure the stable development of business work.