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Data Densification

Visual Analytics offers you the ability to "fill in" missing data in your data set. There are two main types of Data Densification in Visual Analytics:

Domain Padding shows missing records in a range and completes the range in chronological order.
Right click on the date field or numeric bin in the Columns Deck and select Show Missing Values.
Domain Completion completes data by showing all available records.
Right click on the field in the Columns/Rows Deck and select Show Empty Columns/Rows.

Show Missing Values (Domain Padding)

Visual Analytics performs domain padding for date fields and numeric bins and shows missing records in chronological order for date fields and numerical order for numeric bins. For example, in our sample data source, Weeks 7 and 8 are missing. Visual Analytics, by default, does not display the missing weeks and draws a direct line from Week 6 to Week 9. On applying domain padding, Visual Analytics adds the missing weeks based on the surrounding values. You should keep in mind that Visual Analytics is only filling in the missing weeks in the view, and not the missing records.

Show Missing Values (Domain Padding) is available on right-click of the date dimension and bins.

When you apply domain padding to a date dimension, all hierarchies of the same date dimension inherit domain padding. On expanding a hierarchy, Visual Analytics automatically displays the missing values in that hierarchy.

Domain padding for Trend Lines

When displaying Trend Lines, Visual Analytics automatically applies domain padding to the innermost date dimension in the Columns/Rows Deck. In the following example, the innermost date dimension is MONTH(stock_date), and therefore, domain padding is applied to it.

On expanding MONTH(stock_date) hierarchy, Visual Analytics removes domain padding from Months and applies it to DAY(stock_date), which has now become the innermost date dimension in the hierarchy.

Show Empty Rows (Domain Completion)

Domain Completion completes data by showing all available records for the specified dimension based on the unique values in your data set. Let’s consider a scenario where you want to compare the weekly attendance for each student of your class. Now, if a student does not attend a particular lecture for an entire week, the corresponding record might not be present in your data set. On applying domain completion on Period, Visual Analytics completes the record by displaying missing lectures for the students.