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The chart builder is where you build a single chart: choose source, metric, dimension, type, visual customisation.
Chart builder with source, metric, grouping selection and preview

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Chart anatomy

1

Data source

  • Object: Deal, Company, Contact, Task, Invoice, Project, etc.
  • List: start from an existing list (with filters applied)
  • Multiple: union or join of multiple sources (complex charts)
2

Filters

Narrow the data:
  • value > 10000
  • stage in ("Proposal", "Negotiation")
  • created_at in last 90 days
3

Metric

What you measure:
  • count (record count)
  • sum(field) (e.g. total deal value)
  • avg(field) (average)
  • min / max
  • count_distinct (unique)
  • Custom metrics (formula)
4

Group by (dimension)

One or more dimensions:
  • Categorical: stage, owner, industry
  • Date: per day, per week, per month, per quarter
  • Numeric: buckets (e.g. deal value: 0-10k, 10-50k, 50-100k, 100k+)
5

Chart type

Arya suggests the optimal type based on metric and dimension. Override if needed.
6

Visual customisation

Colours, labels, legend, background, value formatting (€, %, K/M).

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Practical examples

Source: Invoice (filter: status = Paid, date in last 12 months). Metric: sum(amount). Group: per month. Type: line chart.
Source: Invoice. Metric: sum(amount). Group: per company.name. Sort: desc, top 10. Type: horizontal bar.
Source: Deal. Metric: count. Group: per stage (ordered). Type: funnel.
Source: Task (filter: overdue=true). Metric: count. Group: per assignee.name. Type: bar chart, colour = priority.
Source: Deal (closed only). Custom metric: count(won) / count(total) * 100. Group: per owner. Type: bar with target.

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Custom metrics (formulas)

For metrics not covered by base aggregators, use formulas: 
weighted_pipeline = sum(value * probability / 100)
conversion_rate = count_distinct(won_deals) / count_distinct(all_deals) * 100
avg_cycle_time = avg(closed_at - created_at)
Supports arithmetic operators, date functions, IF conditions.

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Period comparison

Every chart can show comparison with previous period:
  • Vs previous period (MoM, YoY)
  • Vs set target
  • Vs historical average
Appears as overlay or second series.

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Save and reuse

A saved chart can be:
  • Used in multiple dashboards
  • Shared as “single chart” via link
  • Exported (image, SVG, data)

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Frequently asked questions

Yes. You can enable cache if performance is a concern.
Yes, with join (e.g. deal + company to filter by industry). Mind performance on large datasets.
Arya uses workspace timezone for temporal aggregations. Configurable per chart if needed.