Multi-Source Heterogeneous Data Cell Information Processing Model
Jiadi Chen · 2024
Current data organization methods are difficult to effectively integrate and conduct association analysis on massive multi-source heterogeneous data. To address this issue, this paper introduces a Data Cell Information Processing Model (DCIPM), which considers data cells as the basic units. Entities and transactions are extracted from various multi-source heterogeneous databases and encapsulated with algorithms. By designing multi-level data cells, logical relationships between entities and transactions are constructed to form a comprehensive data cell network. According to the given task requirements, various types of data across different industries are collected and analyzed following specific logical rules without impacting the data structures of databases, and then the desired results are returned. This presents a novel approach for efficiently organizing various types of dispersed heterogeneous data.