Data densification is a largely undocumented aspect of Tableau that can be useful in many circumstances but can also be confusing when encountered unexpectedly. In this article we will provide information about data densification with the intent of dispelling confusion and providing the Tableau author with sufficient knowledge to use this feature to their advantage.
We will begin with understanding Data densification, Sparse Data, Domain Completion, and Domain Padding.
- Data densification: A behavior wherein Tableau displays marks in the view for which there is no corresponding underlying data.
- Sparse data: An intersection of one or more dimensions and one measure for which there is no value.
There are two types of data densification: domain completion and domain padding.
Domain completion is the more complex of the two and can be deployed cleverly to solve sparse data issues, but may also appear unexpectedly and prove a challenge to address.
Domain completion: The addition of marks on a sparsely-populated view that cause all possible dimension/measure combinations to display results.
Grasping domain completion requires a good understanding of dimensions and measures — discrete and continuous — and partitioning and addressing within table calculations.
Now, let’s consider how domain completion can be deployed.
Deployment of domain completion
Domain completion can be activated in numerous and sometimes perhaps surprising and confusing ways. Adjusting the arrangement of pills on the shelves, toggling dimensions between discrete and continuous, switching view types on the
Marks view card, adjusting partitioning, addressing, and other changes can impact domain-completion activation. Let’s understand this with help of an example.
Exercise: Activating domain completion in a
crosstab part I
The following steps will guide you through the Exercise of Domain Completion:
- Navigate to https://public.tableau.com/profile/marleen.meier to locate and…