One Tip That Changed How I Write Deneb Visuals in Power BI

Why Deneb?

If you've hit the ceiling of Power BI's built-in visuals, Deneb is the escape hatch. It lets you write Vega or Vega-Lite specs directly inside Power BI, giving you pixel-level control over your visualisations while still being fed by your data model. It's incredibly powerful — but it can also get messy fast.

After spending a lot of time building dashboards with Deneb, there's one pattern that consistently keeps my specs clean, composable, and easy to iterate on.

The Tip: Think in Layers, Not in Charts

The single most impactful shift you can make in Deneb is to stop thinking of your visual as one monolithic chart and start thinking of it as a stack of independent layers. Vega-Lite's layer construct lets you overlay multiple marks on the same axes, and it's the key to building complex visuals that don't collapse under their own weight.

Instead of trying to cram everything — bars, lines, labels, reference lines, thresholds — into a single mark definition, you split each concern into its own layer. Each layer has its own mark type, encoding, and even its own data transforms. The result is a spec where every visual element is isolated, named (via comments), and independently tuneable.

Example: A Bar Chart with a Target Line and Labels

Here's a common scenario — you want bars showing actuals, a rule mark for the target, and text labels on top. Instead of hacking this into one definition, layer it:

{
  "data": {"name": "dataset"},
  "layer": [
    {
      // Layer 1: The bars
      "mark": {
        "type": "bar",
        "cornerRadiusTopLeft": 4,
        "cornerRadiusTopRight": 4
      },
      "encoding": {
        "x": {"field": "Category", "type": "nominal"},
        "y": {"field": "Actual", "type": "quantitative"},
        "color": {
          "condition": {
            "test": "datum.Actual >= datum.Target",
            "value": "#4CAF50"
          },
          "value": "#EF5350"
        }
      }
    },
    {
      // Layer 2: Target reference line
      "mark": {
        "type": "rule",
        "strokeDash": [6, 4],
        "strokeWidth": 2
      },
      "encoding": {
        "y": {"field": "Target", "type": "quantitative"},
        "color": {"value": "#555555"}
      }
    },
    {
      // Layer 3: Value labels on top of bars
      "mark": {
        "type": "text",
        "dy": -10,
        "fontSize": 11,
        "fontWeight": "bold"
      },
      "encoding": {
        "x": {"field": "Category", "type": "nominal"},
        "y": {"field": "Actual", "type": "quantitative"},
        "text": {
          "field": "Actual",
          "type": "quantitative",
          "format": ",.0f"
        }
      }
    }
  ]
}

Why This Works So Well

• Isolation — Need to tweak the label font size? Go straight to Layer 3. Want to change the target line to a tick mark? Edit Layer 2. Nothing else is affected.

• Readability — When you come back to a spec after two weeks, the layered structure tells you exactly what each piece does. Comments help, but the structure itself is self-documenting.

• Composability — Building a new visual? Start with a single-layer bar chart, confirm it works, then add layers one at a time. Each addition is a small, testable step rather than a rewrite.

• Conditional logic per layer — Each layer can have its own transform block. This means you can filter or calculate data differently for labels vs. marks vs. reference lines, all within one spec.

A Practical Workflow

1. Start with a single layer that plots your primary mark (usually bars or lines).

2. Get the encoding and axes right before adding anything else.

3. Add one layer at a time — reference lines, annotations, labels — and preview after each.

4. Use comments liberally to label each layer's purpose.

5. If a layer's logic is getting complex, consider whether a DAX measure or a Vega calculate transform is the cleaner place to handle it.

Final Thought

Deneb rewards you for being deliberate. The temptation is to jump in and start encoding everything at once, but the specs that survive real-world iteration are the ones built layer by layer. Treat each layer like a function with a single responsibility, and your Deneb visuals will be dramatically easier to maintain and extend.