Fragmented Intelligence Data Management Based on Digital Object Architecture
Tai Peng, Jing Sun · 2023
Fragmented intelligence data is an important piece of information in intelligence research. In actual business, it presents the characteristics of large data volume, various types, different structures, and wide sources and coverage. Under the traditional data management mode, the intelligence business scene data is highly correlated and coupled, but due to the different structure and storage methods of the data, it is difficult to achieve overall deployment, aggregation and sharing of multi-source heterogeneous and fragmented intelligence data. Aiming at these problems, a fragmented intelligence management method based on data objects is proposed, and the digital object system and related technologies are used to realize the view unification, fusion and on-demand sharing of multi-source heterogeneous fragmented intelligence data. An effective solution is provided for the management of multi-source heterogeneous intelligence data resources under the collaborative intelligence research work mode.