During the Map Columns step of the import process, there are fields that MindBridge requires in order to effectively analyze your data, but you can also join columns, split a column, and duplicate column data for more flexibility, as well as add columns for filtering.
When you add columns for filtering, they are not analyzed in MindBridge as part of your analysis, but you can use these columns to find specific data within several analysis results dashboards.
Learn how to add columns that can be used to filter your analysis results in MindBridge.
Add additional columns for filtering
- During the Map Columns step, open the more actions menu ( ) to the right of the desired column.
- Select Add additional column.
A pop-up window appears.
- You have the option to change the column name using the Header Name field.
You will see a preview of the first 2 cells in the selected column, which you can use to ensure you have selected the correct data.
- When you are satisfied, Save your work.
The column will be added for filtering and you will be taken back to column mapping. These columns are displayed below Additional columns, located at the bottom right of this page.
When you add columns for filtering, you will also enable a section on the Data page to Import additional data.
Where will columns for filtering appear?
In general ledger analyses, any columns added for filtering appear in the menus above the graph.
Prior period comparison dashboard
In general ledger analyses, any columns added for filtering appear in the menus near the top of the page.
Risk overview dashboard
Added columns appear as filters on the Risk overview dashboard and in the Risk by graph.
In general ledger analyses and Flex analyses, any columns added for filtering appear in the menus above the table.
Audit assertion risk dashboard
In general ledger analyses, any columns added for filtering appear in the menus above the table.
Data table dashboard
Added columns appear as filters in the filter builder on the data table, as well as sortable columns.
Filtering is designed for categorical columns, and as a result, the number of unique entries in the column must be under 10,000.
Here are some examples of common column headers that are often added for filtering:
- User ID
- Company Code
- Fund ID
- Project ID
- Program ID