收益管理中基于大数据仓库的需求无约束估计:框架与挑战

Demand unconstraining estimation based on big data warehouse in revenue management systems: framework and challenges

现有需求无约束估计方法均为基于公司内部数据仓库中所获需求信息而开发,在当前基于大数据分析的激烈竞争市场环境中,无法满足收益管理系统日益增长的实时需求预测和优化决策分析需要。为了实时、动态地同时获取并分析内部和外部数据资源中有关每位顾客的无约束需求数据,包括结构化和非结构化的信息,提出了以面向收益管理需求无约束估计为主题的大数据仓库框架,并据此讨论了无约束需求知识挖掘以及需求无约束估计商务智能分析工具开发应用过程中面临的各项挑战。

In order to achieve and exam the unconstrained demand data related to each customer in real time and dynamically from both internal and external data resources, including structured and unstructured information, a big data warehouse framework for demand unconstraining estimation in revenue management was proposed. After that, the challenges in unconstrained demand knowledge mining, as well as the process of development and application of business intelligence analysis tools for demand unconstraining estimation were discussed.