Logistics Enterprise Business Intelligence System Framework For Research

With the acceleration of global economic integration and development of information technology, logistics companies have gotten rapid development and growth. These enterprises that provided transportation, warehousing and other services simply and mechanically, expand into those who make more organized and efficient provision of transportation, warehousing and value-added services, meanwhile they begin to take the road of informationization, which can be divided into three steps-data informationization, process informationization and decision informationization. Almost every enterprise realized data informationization. Most enterprises are in the progress of or have completed progress informationization and accumulated a large amount of data in a variety of business systems, which creates conditions for decision informationization. Establishment of business intelligence system is a good choice of achieving decision informationization.Through the survey of a number of logistics companies, we summarized the general data analysis requirements covering that of order processing, transportation, distribution, warehousing, customs clearance, settlement and comprehensive business for BI system from the perspective of core business activities. Then we designed the overall framework of BI and data model framework based on subject domain. In the data model framework, a subject domain was divided into hierarchical structure of several themes, making every subject domain a tree framework. According to requirements analysis, we designed six subject domains including that of order processing, transportation, distribution, warehousing, customs clearance, settlement and comprehensive finance. In every subject domain we built fact tables and dimension tables for the subject instances. Finally, in a practical logistics enterprise, based on the transportation subject domain framework, combined with its transportation management business demands, we designed and created a transportation data mart. Online analyses were carried out on the transportation cube established by extracting data from the data mart. The results were represented and supported by tables and graphs. Different colors and short message platform were used to warn people abnormal results. In addition, the clustering analysis, a kind of data mining technology, was carried out to do the carriers performance evaluation.The framework of BI system will provide reference for logistics enterprises that are taking or will take the road of decision informationization. With their own business needs, logistics enterprises can design and implement BI system quickly based on this framework, and do OLAP or data mining to business data, which aids decision-makers to develop a variety of business decisions, thereby improving overall competitiveness.