Differences Between a BI/Data Warehouse System and an OLTP System-阿里云开发者社区

开发者社区> 数据库> 正文
登录阅读全文

Differences Between a BI/Data Warehouse System and an OLTP System

简介:

. Level of detail: The OLTP layer stores data with a very high level of detail, whereas data in the Data Warehouse is compressed for high-performance access (aggregation).

. History: Archiving data in the OLTP area means it is stored with minimal history. The Data Warehouse area requires comprehensive historical data.

. Changeability: Frequent data changes are a feature of the operative area, while in the Data Warehouse, the data is frozen after a certain point for analysis.

. Integration: In contrast to the OLTP environment, requests for comprehensive, integrated information for analysis isare very high.

. Normalization: Due to the reduction in data redundancy, normalization is very high for operative use. Data staging and lower performance are the reasons why there is less normalization in the Data Warehouse.

. Read access: An OLAP environment is optimized for read access. Operative applications (and users ) also need to carry out additional functions regularly, including change, insert, and delete.

 

 
专注于企业信息化,最近对股票数据分析较为感兴趣,可免费分享股票个股主力资金实时变化趋势分析工具,股票交流QQ群:457394862
分类: SAP BI

本文转自沧海-重庆博客园博客,原文链接:http://www.cnblogs.com/omygod/archive/2011/09/06/2169321.html,如需转载请自行联系原作者

版权声明:本文内容由阿里云实名注册用户自发贡献,版权归原作者所有,阿里云开发者社区不拥有其著作权,亦不承担相应法律责任。具体规则请查看《阿里云开发者社区用户服务协议》和《阿里云开发者社区知识产权保护指引》。如果您发现本社区中有涉嫌抄袭的内容,填写侵权投诉表单进行举报,一经查实,本社区将立刻删除涉嫌侵权内容。

分享:
数据库
使用钉钉扫一扫加入圈子
+ 订阅

分享数据库前沿,解构实战干货,推动数据库技术变革

其他文章
最新文章
相关文章
展开