Incremental data extraction model of distribution network user business expansion based on improved IAA algorithm

When providing services for distribution network users, the throughput of expanded data of user industry is low, which leads to long data extraction time. Therefore, an incremental data extraction model for expanded data of distribution network users based on improved IAA algorithm is proposed. Based on the sparsity analysis results of the data of distribution network users' business expansion and installation, the improved IAA algorithm is used to incrementally learn the original data, import it into the data warehouse, read multi-source data, build an incremental data extraction model, compare the data reading speed and update speed of the distribution network users' business expansion and installation system, determine the data extraction time window, and extract incremental data. The experimental results show that the data throughput of this model and the time-consuming part of data extraction are improved, which provides a new idea for incremental data extraction.