金融业数据仓库中星型衍生子维度模式  

Derived sub-dimension schema from the star in financial data warehouse

作　　者：汪辉[1] 梁小满[1] 

机构地区：[1]衡阳师范学院计算机科学系,湖南衡阳421002

出　　处：《湖南科技大学学报（自然科学版）》2013年第1期80-83,共4页Journal of Hunan University of Science And Technology：Natural Science Edition

基　　金：湖南省科技厅资助项目(2011GK3033)

摘　　要：数据仓库建模是构建数据仓库的核心,通常采用维度模型的建模方式.分析了维度模型中星型模式和雪花模式的优缺点,并针对金融业数据仓库特点,以证券业务为例,提出了星型衍生子维度模式概念,阐述了此结构的生成条件、算法和优点,即在典型的星型模式中,对大维度表中基数较小的相对独立的维度属性进行分解,生成子维度表,用代理键将其与父维度表及事实表关联,这有利于数据装入、提高数据仓库综合查询效率及一定程度上减少数据冗余,这对于金融业数据仓库中多主题的数据建模具有实际应用价值.Modeling was the core of data warehouse building, and the dimensional modeling technique was generally adopted. After analyzed the advantages and drawbacks of star and snowflake schemas in dimensional modeling, the securities business was taken as an example, the concept of a derived sub - dimension schema was proposed from the star according to the features of financial data warehouse, stated the conditions, algorithms and advantages of the structure. In the typical star schema, for the large dimension table, the relative independent field with low cardinality was broken into sub - dimension tables, which were associated with the super - dimension and fact tables by surrogate keys. The structure benefits data loading, improving query performance of data warehouse, and decreasing of data redundancy to some extent. It is practical valuable in multi -subject financial data warehouse modeling.

关 键 词：数据仓库 维度模型 星型模式 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]