Asset Intelligence: From Points to Dashboard

This tutorial turns a raw asset table into a decision dashboard: clean the attributes, bin the points into hexagons, add a density surface, and assemble the widgets into a dashboard. It uses the SQL Workspace, the H3 Grid plugin, and the Processing toolbox.

1. Load the assets

Add your asset points (CSV with coordinates, GeoJSON, GeoPackage, or a spatial database — see Adding Data).

2. Clean and enrich the attributes

Use the Field Calculator or the SQL Workspace to derive what the dashboard will need, for example:

SELECT *, install_year, status
FROM assets
WHERE status IN ('active', 'degraded');

Computed columns such as age bands or category codes make the later widgets trivial to configure.

3. Bin the points into hexagons

Enable the H3 Grid plugin and create an H3 grid over the data extent at a resolution that matches your reading distance, then bin the asset points into the cells. Each hexagon now carries an aggregate count — the first real answer of the analysis.

4. Add a density surface

Run Processing → Spatial Statistics → Kernel Density on the raw points. Where the hexagons answer “how many per area”, the density surface answers “where is the pressure concentrated”, and the two together are easy to read.

5. Assemble the dashboard

1. Open Processing → Dashboard and add panels for the hexagon counts and the density layer.
2. Add a Chart Widget Grid for category breakdowns from the attribute table.
3. Keep the Statistics panel open for live summary numbers as you filter.

6. Publish it

Save the project as a template for the monthly refresh, or use Export As HTML to publish the dashboard as a read-only view.

Next steps

• With a timestamp on the assets, run Processing → Spatial Statistics → Emerging Hot Spot Analysis to see which bins are heating up.
• Use Route Animation to replay field movements on top of the dashboard.