This is the heart of the process. We're going to write a Vega-Lite specification. It looks like code, but it's really just a set of instructions describing your visual. We'll create a simple choropleth map, where each country is colored by its sales value.

First, we need to tell Deneb where to find our GeoJSON file. In the "Config" tab, you can define a URL to your GeoJSON. This is the cleanest method.

The Specification: A Choropleth Map

Go to the "Specification" tab, delete the boilerplate code, and paste this in. We'll break it down below.

{
  "data": {
    "url": "https://your-url/to/your-countries.json",
    "format": {
      "property": "features"
    }
  },
  "projection": {
    "type": "mercator"
  },
  "transform": [
    {
      "lookup": "properties.iso_a2",
      "from": {
        "data": {
          "name": "dataset"
        },
        "key": "Country Code",
        "fields": ["Total Sales", "Country Name"]
      }
    }
  ],
  "mark": {
    "type": "geoshape",
    "stroke": "white",
    "strokeWidth": 0.5
  },
  "encoding": {
    "color": {
      "field": "Total Sales",
      "type": "quantitative",
      "scale": {"scheme": "blues"}
    }
  }
}

Breaking It Down

• "data": We point to our GeoJSON file via a URL. "property": "features" tells Vega-Lite to look for the array of shapes inside that file.
• "projection": This defines how the 3D globe is flattened onto your 2D screen. `mercator` is a web standard.
• "transform": This is the magic! The lookup is like a VLOOKUP or a JOIN. It says: "For each shape in the GeoJSON, look at its properties.iso_a2 value. Find the matching value in the Power BI dataset's Country Code column. When you find a match, pull in the Total Sales and Country Name fields."
• "mark": We tell it to draw a geoshape for each feature.
• "encoding": This connects the data to the visual properties. We're telling it to encode the color of each shape based on the `Total Sales` field, treating it as a quantitative value and using a blue color scheme.

Make sure to replace the URL, lookup keys (`properties.iso_a2`, `Country Code`), and field names (`Total Sales`, `Country Name`) with your own.

Step 4: Adding Interactivity and Rich Tooltips

A static map is nice, but an interactive one is powerful. Let's add two essential features: tooltips and zoom/pan functionality.

Creating Rich Tooltips

A good tooltip provides context at a glance. In your Vega-Lite spec, add a `tooltip` property to your `encoding` block. It takes an array of fields you want to display.

Modify your `encoding` block to look like this:

"encoding": {
  "color": {
    "field": "Total Sales",
    "type": "quantitative",
    "scale": {"scheme": "blues"}
  },
  "tooltip": [
    {"field": "properties.name", "type": "nominal", "title": "Country"},
    {"field": "Total Sales", "type": "quantitative", "format": ",.0f"}
  ]
}

Now when you hover over a country, you'll see its name and formatted sales value. Easy, right?

Enabling Zoom and Pan

To let users explore the map, we can add zoom and pan controls with a `selection` property. Add this block to the top level of your JSON spec (at the same level as `projection` and `mark`).

"selection": {
  "grid": {
    "type": "interval",
    "bind": "scales"
  }
}

This simple block tells Vega-Lite to create an "interval selection" that is bound to the scales of the visual. In plain English, it means you can now use your mouse wheel to zoom and click-and-drag to pan around the map. It's a huge win for user experience with minimal effort.

Step 5: Leveling Up with Advanced Layers

The true power of Deneb comes from its ability to layer visuals. You're not limited to a single choropleth. You can stack marks on top of each other.

Let's say you want to plot your office locations as circles on top of the sales map. To do this, you'll need a dataset with office names, latitudes, and longitudes.

The structure involves converting your spec to use a `layer` array. Each object in the array is a complete visual specification that shares the same space.

Here’s a conceptual structure:

{
  "projection": { ... },
  "layer": [
    {
      // This is your entire choropleth map spec from Step 3 & 4
      "data": { ... },
      "transform": [ ... ],
      "mark": "geoshape",
      "encoding": { ... }
    },
    {
      // This is the new layer for city points
      "data": {"name": "dataset"},
      "mark": "circle",
      "encoding": {
        "longitude": {"field": "Office Longitude", "type": "quantitative"},
        "latitude": {"field": "Office Latitude", "type": "quantitative"},
        "size": {"value": 100},
        "color": {"value": "red"}
      }
    }
  ]
}

In this example, the first layer is our choropleth map. The second layer reads longitude and latitude fields from your Power BI dataset and plots them as red circles on top of the map. This layering technique is incredibly versatile—you can add flight paths, text labels, heatmaps, and more.

Your Journey Has Just Begun

We've covered the five fundamental steps to get you building powerful, custom maps in Power BI with Deneb:

1. Prepare your GeoJSON with the right join key.
2. Set up your Deneb canvas with the necessary data fields.
3. Write a basic Vega-Lite spec using a `lookup` transform.
4. Add interactivity with tooltips and zoom/pan selections.
5. Explore advanced techniques like layering multiple marks.

This is your launchpad. The world of Vega-Lite is vast, and the best way to learn is by experimenting. Tweak the colors, try different mark types, and explore the extensive Vega-Lite documentation. You now have the framework to stop saying "I wish Power BI could..." and start building exactly what you envision. Go create something amazing!