从关系OLTP数据库到OLAP多维数据集的最佳方法是什么？ [英] What is the best approach to get from relational OLTP database to OLAP cube?

问题描述

我有一个相当标准的OLTP标准化数据库，我意识到我需要做一些复杂的查询，平均值，在数据中的不同维度的标准差。

I have a fairly standard OLTP normalised database and I have realised that I need to do some complex queries, averages, standard deviations across different dimensions in the data.

所以我已经转向SSAS和创建OLAP多维数据集。

So I have turned to SSAS and the creation of OLAP cubes.

但是，为了创建多维数据集，我相信我的数据源结构需要是一个星或 '配置（我不认为现在是这样）。

However to create the cubes I believe my data source structure needs to be in a 'star' or 'snowflake' configuration (which I don't think it is right now).

是正常的程序使用SSIS在我的主OLTP数据库做一些类型的ETL过程另一个关系数据库，它是在正确的星配置的事实和维度，然后使用此DB作为OLAP多维数据集的数据源？

Is the normal procedure to use SSIS to do some sort of ETL process on my primary OLTP DB into another relational DB that is in the proper 'star' configuration with facts and dimensions, and then use this DB as the datasource for the OLAP cubes?

推荐答案

是的，这是基本的想法。您将取得高度标准化的OLTP数据库，并将其反标准化为多维数据集，以便对数据进行切片和切片，然后对其进行报告。逻辑设计技术被称为维度建模。有关尺寸建模的大量信息，请访问 Kimball Group 。 Ralph Kimball的关于此主题的图书也很好。如果您想要详细了解BI工具本身，请查看虚拟实验室在SSIS，分析服务等。

Yes, that is the basic idea. You take your highly normalized OLTP database and de-normalize it into cubes for the purpose of slicing and dicing the data and then presenting reports on it. The logical design technique is called dimensional modeling. There is a ton of great information about dimensional modeling over at the Kimball Group. Ralph Kimball's books on the subject are also excellent. If you want to learn more about the BI tools themselves, check out the virtual labs on SSIS, analysis services and more.

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