什么dw模式是适当的，当没有措施？

问题描述

所有的演示都在他们的例子中使用销售/订单模型作为衡量标准。但是我的数据库不是事务性的。这是一个以客户为中心的模型，其中有一个表连接到几个属性表。

由于不同的模型，这甚至不符合多维数据集建立的资格，还是有一些方法仍然可以构建立方体，尽管它不是事务性的？

我听说过无数的事实表，但还没有真正理解这个概念。这是你会使用哪一个？

解决方案

您要分析什么样的指标？

如果你想做的是聚合具有特定属性的客户数量，你可以使用这样的事实表：

  Customer_FK，Attribute_FK 
  

我更喜欢使用固定值为1的额外列使汇总更简单

  Customer_FK，Attribute_FK，Attribute_count 
 1000,23,1 
 1001,23,1 
  

这样可以在第三列中使用一个简单的汇总来了解你有2个客户属性＃23。

我假设您将使用单个（平面）属性维度表，并将其与以客户为中心的数据库中的几个属性表进行填充。 / p>

All the demos out there use a sales/order model as a measure in their examples. But my db is not transactional. It's a customer-centric model where there is one table for the customer which is joined to several attribute tables.

Does this not even qualify for cube building because of the different model, or is there some way to still build cubes despite it not being transactional?

I've heard of factless fact tables but don't really understand the concept yet. Is this where you would use one?

解决方案

What kind of metrics are you going to analyze?

If all you want to do is aggregate the number of customers that have a particular attribute, you could get away with a fact table like this:

Customer_FK, Attribute_FK

I prefer using an extra column with a fixed value of "1" to make aggregation simpler

Customer_FK, Attribute_FK, Attribute_count
    1000,      23,             1
    1001,      23,             1

This way you can use a simple sum aggregation on the third column to find out that you have 2 customers with attribute #23.

I am assuming you would use a single (flat) attribute dimension table and populate it with the several attribute tables from your customer-centric db.

http://www.kimballgroup.com/1996/09/02/factless-fact-tables/

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