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Building Charts

Starter+

Charts are the building blocks of every CalabiIQ dashboard. Each chart is built from a single dataset, configured with metrics, dimensions, and visual settings in the Chart Editor.

Creating a Chart

From the Charts list

  1. Navigate to Charts in the top navigation.
  2. Click + Chart.
  3. Select a Dataset from the dropdown (e.g., psychometric_reporting.scores).
  4. Choose a Chart type and click Create new chart.

From a Dataset

  1. Navigate to DataDatasets.
  2. Find the dataset you want to visualise.
  3. Click the Explore icon (bar chart icon in the Actions column).
  4. The Chart Editor opens pre-configured with that dataset.

From SQL Lab

After running a query, click Explore in the results toolbar to build a chart from the query results. See SQL Lab for details.


Chart Types Overview

CalabiIQ provides a rich library of chart types. Select the right one for your data shape and the story you want to tell.

Chart TypeBest ForTypical DimensionsTypical Metrics
Bar ChartComparing values across categories1 categorical1–3 numeric
Line ChartTrends over timeTime column1–5 numeric
Area ChartCumulative trends over timeTime column1–3 numeric
Pie ChartPart-to-whole proportions (≤ 7 slices)1 categorical1 numeric
Big NumberSingle KPI with optional trend line1 numeric
Big Number with TrendlineKPI + sparkline contextTime column1 numeric
TableTabular data with sorting and searchAnyAny
Pivot TableCross-tab analysisRow + column dims1 numeric
Scatter PlotCorrelation between two numeric columns1 entity dim2 numeric
HeatmapDensity / intensity across a grid2 categorical1 numeric
Funnel ChartConversion / drop-off analysis1 categorical (ordered)1 numeric
Gauge ChartProgress toward a target1 numeric
World MapGeographic distributionCountry/ISO column1 numeric
Bubble ChartThree-variable comparison1 entity dim3 numeric
HistogramDistribution of a numeric column1 numeric
Box PlotStatistical spread (quartiles, outliers)1 categorical1 numeric
TreemapHierarchical part-to-whole1–3 categorical1 numeric
SunburstNested hierarchies2–4 categorical1 numeric
Calendar HeatmapDaily patterns over a yearDate column1 numeric
Mixed ChartBar + line on same axisTime column2+ numeric
Tier availability

Advanced chart types (Scatter, Heatmap, Funnel, World Map, Bubble, Histogram, Box Plot, Treemap, Sunburst, Calendar Heatmap) require Professional tier or above.


Chart Editor Walkthrough

The Chart Editor is divided into three panes:

┌──────────────────────────────────────────────────────────┐
│ Dataset & Chart Type selector (top bar) │
├──────────────┬───────────────────────────────────────────┤
│ │ │
│ Config │ Chart Preview │
│ Panel │ (updates on Run) │
│ (left) │ │
│ │ │
└──────────────┴───────────────────────────────────────────┘

Config Panel sections

SectionPurpose
TimeSet the time column, time grain (day/week/month/year), and time range filter
QueryDefine metrics, dimensions (Group By), filters, and row limit
Columns(Pivot Table only) Define column groupings
CustomizeVisual settings: colors, labels, legend position, number formatting
Advanced AnalyticsRolling averages, time comparisons, resampling
AnnotationsAdd reference lines, event markers, or shaded regions

Configuring Metrics

A metric is an aggregation applied to a column. In the Query section:

  1. Click + Add metric.
  2. Choose an aggregate function from the dropdown: COUNT, COUNT DISTINCT, SUM, AVG, MIN, MAX.
  3. Select the target column.
  4. Optionally, enter a custom SQL expression for advanced calculations.
  5. Give the metric a readable label (e.g., Avg Score).

You can also use saved metrics defined on the dataset (shown with a bookmark icon). See Metrics.

Configuring Dimensions

Dimensions are columns used to group data (the X-axis of a bar chart, the rows of a table, etc.).

  1. In the Query section, click the Dimensions field.
  2. Search for and select one or more columns.
  3. For time-series charts, set the Time column and Time grain in the Time section.

Adding Filters

Chart-level filters limit the data queried for this chart only (unlike dashboard filters which apply broadly).

  1. In the Query section, click + Add filter.
  2. Select a column, an operator (=, !=, IN, BETWEEN, IS NOT NULL, etc.), and a value.
  3. Click Save on the filter row.

Multiple filters are combined with AND logic by default.

Advanced Analytics

OptionWhat it does
Rolling averageSmooths noisy time series with a moving window (configurable period)
Time comparisonPlots a second series shifted back by a period (e.g., "vs 4 weeks ago")
ResamplingAggregates data to a different grain (e.g., daily → weekly 7D)
CumulativeReplaces each value with the running total

Running and Updating a Chart

  • Click Run (or press Ctrl+Enter) to execute the query and refresh the preview.
  • Changes to the Config Panel do not auto-refresh the chart — you must click Run manually.
tip

Use the Row limit dropdown in the Query section to speed up iterations during configuration. Set it back to the desired limit before saving.


Saving a Chart

  1. After configuring the chart and clicking Run to confirm the output looks correct, click Save (top-right).
  2. Enter a Chart name.
  3. Choose whether to Add to dashboard immediately.
  4. Click Save & go to dashboard or Save.

Saved charts appear in the Charts list and can be added to any number of dashboards.


Adding a Chart to a Dashboard

From the Chart Editor:

  1. Click ···Add to dashboard.
  2. Search for the dashboard by name.
  3. Click Add.

From a Dashboard in Edit mode:

  1. Find the chart in the right-hand Charts panel.
  2. Drag it onto the canvas.

Editing an Existing Chart

  1. Open the dashboard containing the chart.
  2. Hover over the chart and click the pencil (Edit) icon.
  3. This opens the Chart Editor with the chart's saved configuration.
  4. Make your changes, click Run, then Save.

All dashboards using this chart will automatically reflect the update.