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Build visualizations with drag-and-drop

Written by Alvys Admin

Summary

The visualization on a dashboard is close, but you want a slight variation — maybe filter by Carrier instead of Customer, or change the chart from columns to a line. You'll do this by dragging items from the Analytics Catalog into the bucket drop zones — no code required. This page walks through the drag-and-drop flow with a full worked example, then covers how to save your work.

The Analytics Catalog is rich. Your tenant has hundreds of pre-built metrics, facts, and attributes covering trips, revenue, cost, on-time performance, miles, drivers, and more. Before you ever reach for a custom formula, search the Catalog — the metric you want is almost always already there.

Open a saved visualization

From the Custom Reports sidebar, click Create visualization.

In the Visualization Designer, click Open in the top toolbar.

Notion Image

The dialog lists every visualization saved on your tenant. Search by name. Click one to load it into the canvas.

Change a saved visualization

Once the visualization is loaded, you can do anything you'd do when building from scratch:

  • Drag a different metric or attribute into a bucket.

  • Remove an item by clicking the × on its chip, or dragging it out of the bucket onto the canvas.

  • Switch chart types by clicking a different chart-type icon at the top of the canvas.

  • Open the Configuration panel to change axes, legend, colors, formatting.

The canvas updates live so you can see your changes immediately.

A worked example — monthly revenue & load count by subsidiary

Most of what you'll ever build can be done with drag-and-drop. Here's a complete walkthrough of building a pivot table that shows Total Revenue and Load Count broken down by month and subsidiary.

Step 1 — Add the metrics

From the Analytics Catalog on the far left, drag the following into the Metrics bucket:

  • Total Revenue

  • Load Count

The canvas updates as you drop each one.

Step 2 — Add the row breakdown

Find the date attribute Load Invoiced At in the Catalog and drag it into the Rows bucket. Click the chip in the bucket and pick Group by → Month so each row represents one month.

Step 3 — Add the column breakdown

Find the Subsidiary attribute in the Catalog and drag it into the Columns bucket. The canvas becomes a pivot table — one row per month, one column per subsidiary, with Total Revenue and Load Count values in each cell.

Step 4 — Add a Subsidiary filter

Drag the Subsidiary attribute up into the filter bar at the top of the Designer. A filter popover opens — pick the subsidiaries you want to see and click Apply. The table now shows only the subsidiaries you picked.

Step 5 — Add totals across months and subsidiaries

Hover over the Subsidiary column header. Click the (three-dot) menu and pick Rollup (total). A totals row and totals column appear, rolling up Total Revenue and Load Count for every subsidiary and every month.

Notion Image

That's a complete visualization built without writing a single formula. Save it (next section), drop it onto a dashboard, and you're done.

Save — overwrite or save as new

You have two save options in the toolbar:

  • Save — overwrites the existing visualization with your changes. Every dashboard that uses this visualization now shows the new version. Save is available only if you authored the visualization — when you open someone else's visualization, the Save option is hidden and only Save as new is offered.

  • Save as new — creates a separate visualization with a new name. The original is untouched.

⚠️ Be careful with Save. If you overwrite a visualization that's used on dashboards built by other people on your team, they'll see your change too. When in doubt, Save as new instead.

After saving, the visualization is available in the Analytics Catalog and can be dropped onto any dashboard.

Tips

  • Search the Catalog first. If you're about to build a chart, the metric or attribute you need is almost certainly already there.

  • Don't overwrite team-used visualizations. Save as new if you're not sure who else relies on it.

  • Start with one metric and one attribute to make sure the chart shape makes sense before piling on more.

Where to go next

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