Notes when creating a Multidimensional Dataset dimension

An important difference between multidimensional data and two-dimensional data in common relational databases is that there are some additional

 

Dimension, that is, adding more conditions to data display. Therefore, the dimension concept in a multi-dimensional dataset is

 

It is very important that we have recently reached the Data Warehouse. It may be said that the data mart is more specific, that is, some

During initial creation of multi-dimensional data, the selection of dimensions may not be so well set. Most of the time we use

First set some clearly visible dimensions, and there may be many dimensions closely related to the multidimensional data of this topic.

We have not yet thought that this is not too urgent. We can first establish these sporadic dimensions, and then combine the theme in

In actual application, we need to gradually improve those dimensions.

However, in the process of establishing a dimension, it is very important to clarify the level of the dimension, which I think is vague.

Currently, many tools that help you build a data warehouse are automatically used to search for layers in a dimension based on the dimensions you provide.

Do not select the correct one or reverse the order of the level. The obtained results will make you unable to understand, clearly in the basic database.

The data is correct. Why is there a problem in the data warehouse?

An easy mistake is that the hierarchy is not clear or the fault occurs. In this case, when the tool is processing

Of course there will be problems.I think it is used to establish these dimensional relationships and divide the internal layers of dimensions. UML Tool or Visio Wait until these

Create a fact table and a dimension table. We recommend that you back up the table every time you change the table. In this way, you can compare the problem with the following picture.

The problem will be solved, and it will be helpful for Data Warehouse Construction.