Summary: A pivot table cross-tabulates your data across two dimensions at once — one dimension spreads across the top as columns, one or more run down the side as rows, and each cell shows the measure value for that combination (for example, meetings booked by campaign and by month).
Who this is for: Anyone who wants to compare a metric across two dimensions in a single view — rep performance by month, statuses by campaign, revenue by source and segment.
Before you start
Pivot tables are built in the Data Explorer. If you're new to it, start with the general guide: How to Build a Chart with the Data Explorer in Alta.
You need at least one measure (the number you're counting) and two dimensions (the fields you're splitting it by). With only one dimension, a regular table or bar chart is usually the better fit.
Step 1 — Open the Data Explorer
In the sidebar, go to Explore → Data Explorer. (You can also edit an existing dashboard widget to change it into a pivot table.)
Pick your data and add the measures and dimensions you want to analyze, exactly as you would for any other chart.
Step 2 — Choose the Pivot Table visualization
In the visualization picker, select Pivot Table (you'll find it grouped with the other tabular visualizations, next to Table and Trend Table).
Alta pre-fills the layout for you: your date field or first breakdown becomes the Columns dimension, your remaining dimensions go to Rows, and all selected measures go to Measures. You can rearrange everything in the next step.
Step 3 — Configure Columns, Rows, and Measures
The pivot table editor has three fields:
Columns — a single dimension whose values spread across the top of the table. A time dimension (month, week) or a short category list works best here.
Rows — one or more dimensions listed down the left side. Each value becomes an expandable row group.
Measures — click Add measure to choose the value(s) shown in each cell.
Step 4 — Choose how multiple measures are laid out
If you add more than one measure, a Measures as selector appears with three options:
Columns (default) — each column value gets a sub-column per measure, side by side.
Rows: measures first — the table is grouped by measure first; expand a measure to see its breakdown by your row dimensions. Each measure gets its own total row.
Rows: measures last — the table is grouped by your row dimension first; expand a row value to see each measure underneath it.
Step 5 — Read the table
The Total row at the top shows the overall value per column, before any row breakdown.
Click a row group to expand or collapse its values.
The first column is pinned, so it stays visible while you scroll horizontally across many columns.
Cell values follow each measure's own value format (number, percent, currency), so mixed-measure tables stay readable.
When you're happy with it, save the chart to a dashboard like any other Data Explorer visualization.
Tips and common pitfalls
Empty table? The pivot table only renders once you've set the Columns dimension and at least one measure. If either is missing, you'll see an empty state.
Column order is alphabetical. Column values are sorted A→Z. For time-based columns, use a proper date/time dimension so the periods are labeled consistently.
Multiple Rows dimensions stack, they don't nest. Each dimension you add to Rows appears as its own separate set of groups (e.g. all campaigns, then all reps) — not as campaign × rep combinations. To cross two dimensions against each other, put one in Columns and one in Rows.
Blank values show as N/A. Prospects or records with no value for a row dimension are grouped under N/A rather than dropped.
No total rows in "Rows: measures last". If you need per-measure totals with measures shown as rows, use Rows: measures first instead.
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