Databases Reference
In-Depth Information
In the previous screenshot, we can see how the fact table (that is, the
Main Data
table) is directly associated with all of the other dimension tables. The purpose of
these dimension tables is to provide context to the values stored in the fact table.
Furthermore, the dimension tables are not only associated with the fact table, but at
the same time they are indirectly associated with each other through the fact table.
With the data model shown we can, for instance, cross-reference the
Origin Airport
with the
Destination Airport
(via the
Main Data
table) and get the
Distance Interval
value between any two of them. These three fields are stored in three different
dimension tables in the data model, and the fact that they are associated allows
QlikView to naturally perform this cross-dimensional reference and support the
associative analysis we just described. This is shown in the following screenshot:
In an associative data model, any field can act as a dimension in a chart. They can all
be used within expressions to aggregate their data too.
Guidelines for table associations
In order to design and build a data model in QlikView, we need to understand how
the associations between tables are created. We also need to consider some basic
rules to avoid performance and data consistency issues. In this section, we will
describe and review these guidelines.
