This article applies to the following Customer Insights roles: Developer
Dimensions specify the data you want returned; more specifically, and using database terminology, dimensions return specific fields from specific tables. You use dimensions to define the information you want your query to bring back. For example, if you’re using the Profile Dim Explore, you can return information about user ages, email domains, and genders. Those three items - Age, Email Domain, and Gender - are the dimensions for the Profile Dim Explore.
Adding a dimension to an Explore is remarkably easy. (In fact, it can sometimes be a little too easy: it’s possible to inadvertently add a dimension that you didn’t want to add.) To add a dimension, just click the field name in the Explore pane:
Believe it or not, that's it.
As long as we're on the subject, dimensions can be added either from the All Fields tab or from the Dimensions tab. The All Fields tab shows both dimensions and measures; by default you need to expand each Dim and Fact in order to access those items. By comparison, the Dimensions tab doesn’t show any of the measures, but it does “pre-expand” each Dim and Fact:
You can also locate dimensions by using the Search field. For example, suppose you know that there’s a dimension named Au Format Date, but you aren’t sure where to find that dimension. In that case, type au in the Search field and then press ENTER. In turn, Customer Insights will show you all the fields that have the string value au anywhere in their name:
Note. After searching for a field name, click the X to reset the fields list.
After you’ve located the desired dimension you can add it to your dataset simply by clicking the dimension name. When you do that, the background color of the dimension turns white, and the dimension appears in the Data section:
And yes, that is easy. The only tricky part is the fact that, when you run your mouse over a dimension, little buttons labeled Pivot and Filter appear. Clicking either of those buttons will not add the dimension to the Data section. Instead, and depending on the button you clicked, your Explore will use the dimension as either a pivot or a filter. If either of those buttons changes color, you know you goofed:
Fortunately, it’s easy to undo a mistake like this. Did you accidentally click the Pivot button, or did you inadvertently click the wrong dimension name? Don’t worry about: just click the button (or the dimension name) a second time and it will be removed from the query:
In other words, click once to enable something, click a second time to disable it.
And what do you do after you finish adding dimensions? Well, one thing you can do is click Run and retrieve some data. For example, here’s the returned data from a simple little query that returns the names of all the countries in the database:
As noted, this query returns the different country names that are stored in our database. That can be useful information. However, what might really be useful would be to know how many users we have from each of these countries. That’s where measures enter the picture.
To remove a dimension, hover the mouse near the right end of the dimension, click the Settings icon, and then click Remove: