Analyzing and Updating Data with Pivot Tables

Rearranging Fields

Dragging a field from Rows to Columns rotates the entire table. Swapping Category for Store changes the grouping dimension. Adding a second field to Rows creates a nested breakdown. It is how fast you can move from one view to another.

The Filters Area

The Filters area adds a dropdown above the entire pivot table. Unlike filtering within Rows or Columns — which narrows what appears in the table structure — a report filter applies to the whole analysis. Every number in the pivot changes to reflect only the selected value.

Removing a Field

Drag it out of the zone.

Click the field pill in the Rows, Columns, or Values area and drag it away — outside the drop zones entirely. Release and the field is removed. The pivot table updates instantly.

Uncheck in the field list.

In the upper part of the PivotTable Fields panel, uncheck the checkbox next to the field name. It is removed from wherever it was placed — Rows, Columns, or Values — in one click.

Refreshing

A pivot table does not update automatically when the source data changes. It holds a snapshot of the data as it was when last refreshed. Adding new rows, correcting values, or deleting records in the source table has no effect on the pivot until you explicitly refresh it.

Go to PivotTable Analyze tab → Refresh. Or right-click anywhere inside the pivot table and choose Refresh.

Task

You will now extend your PivotTable analysis by reorganizing fields, refreshing data, and applying filters.

1. Reorganize the analysis by store

   Remove Category from Rows and drag Store into Rows. Keep Revenue in Values.
   
   

   You should now see total revenue grouped by store.

2. Change layout (Rows → Columns)

   Move Store from Rows to Columns.
   
   

   The PivotTable now displays stores as columns instead of rows.

3. Add a second level (Salesperson)

   Drag Salesperson into Rows.
   
   

   Your PivotTable should now show:

   • Rows — Salesperson
   • Columns — Store
   • Values — Revenue

   This creates a multi-level view of revenue by store and salesperson.

4. Add new data and refresh

   Go back to your dataset and add a new row with:

   • Order Date - 03.12.2026
   • Product — Wireless Mouse
   • Category - Accessories
   • Units Sold — 15
   • Revenue — 450
   • Salesperson — Sarah Thompson
   • Store — Central Mall

   Return to the PivotTable, click inside it, and select PivotTable Analyze → Refresh.

5. Apply a report filter

   Drag Salesperson into the Filters area. Use the filter dropdown above the PivotTable and select Emily Carter.
   
   

   The table will now display only her sales across stores.

6. Interpretation check

   Identify which store generated the highest revenue for Emily Carter. Then switch between All Salespeople and the filtered view to observe how totals change.