Tables in Analytical Designer can have up to 20 attribute rows and 20 attribute columns to refine data in your insight. The data is then merged according to the attribute order in the Rows/Columns sections.

Tables have the following sections: Metrics, Rows, Columns, and Configuration.

Tables can also:

  • Display the values as a percentage.

  • Compare your data to the previous period or same period of the previous year. For details, see Time over Time Comparison.

  • Group data when sorted by the first item in the Rows section.

  • Change the orientation of the table.

If you are using metrics, set the orientation of the table in Configuration > Metrics > Position. You can also change the orientation of the table by swapping attributes between the Rows and Columns sections.

If there are no attributes in the Rows section, you can also use Configuration > Column Headers > Position to change column headers into row headers and vice versa.

For information about common characteristics and settings of all insights, see Insight Types.

Column width

Tables automatically adjust the width of all the columns according to the cell content. The size is calculated according to the content in the header of the column that represents the lowest level of the grouped attributes.

You can also resize each column manually by dragging the edge of the column in a header.

  • To resize all columns in your insight at once, hold the Windows/Command button while dragging.
  • To resize all columns of one metric at once, hold the Alt/Option button while dragging.
  • Double-click the edge of the column to resize to the default size of the column.

Multiple date attributes

Tables support multiple date attributes. For each date attribute, you can select a different date dimension to analyze your data with various date contexts.

For example, you can display when individual customers ordered your products and when the invoices were paid.

When you filter the whole insight by date, you can select any dimension that is available.

Aggregate data

You can aggregate data in a table using the following functions:

  • Sum
  • Max
  • Min
  • Avg
  • Median
  • Rollup (Total)



  1. Create a table in Analytical Designer. For details, see Create Insights.

  2. Hover the mouse over a column header. A burger icon displays on the left side of the header. 

  3. Click the burger icon and select a function. A new row with the function name and appropriate values under the column is displayed.


  • You can add functions for all columns or for individual attributes or metrics - hover your mouse over column headers to display the burger icon. The following image shows the Sum function added in the Year attribute and the Avg function added in the Checkouts metric.

  • If you have multiple items in the Rows section, you can apply the function to all rows (grand total) or to individual attributes from the Rows section (subtotals).

  • To delete a function, click the burger icon and click an already-selected function (with a tick sign) to hide the function row.

Rollup (Total)

Rollup totals are “smart” aggregations.

They are useful for tables that display metrics representing average values, for example, to avoid aggregations like averages of averages.

See the following examples:

  • For the Won metric, the rollup represents the sum of all regions' won amounts.  Sum and Rollup (Total) are equal. 
  • For the Avg. Won metric, rather than take the average of the row’s values (which are already averages), the rollup averages the original underlying data—before it was aggregated by the Won metric and broken into the East Coast and West Coast regions by the Region attribute.  The value of the Avg (an average of averages) differs from the Rollup (Total) average (an average based on the original data). 


  • If you show metrics in rows, you can display up to 1000 data elements horizontally. Similarly, if metrics are arranged in columns, the data element limit applies vertically.

  • Sorting is not available in rows containing metrics.

  • If you change column headers into row headers, the columns that were manually resized return to their default width. This cannot be further modified manually.