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AI DASHBOARD CREATOR

Create dashboards from context,
not from scratch.

Scalar Analytics gives your team an intelligent first dashboard draft, so they can focus on decisions, not setup.

Guided 4-step creation flow Real data previews for suggested widgets Copilot refinements without leaving the wizard
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AI DASHBOARD CREATOR

From dataset context to dashboard in guided steps

Turn semantic mapping and dataset descriptions into a ready-to-edit dashboard proposal with widgets, tabs, global filters, and a conversational copilot.

Instead of starting from a blank canvas, teams begin with a curated first draft generated from business context and real dataset structure.

8-15 suggested widgets with real previews
2-5 theme-based tabs when needed
2-6 global filters proposed automatically
Live memory-scoped copilot for refinements
✓

Only datasets with description and semantic mapping appear ready for AI generation.

✓

The first draft prioritizes KPIs, time series, rankings, distribution, and detail views.

✓

When there are many widgets, AI groups them into business-oriented tabs instead of visual-type clusters.

✓

Date and categorical filters are proposed from the fields that matter most to the selected widgets.

01 Dataset Check readiness
02 Widgets Suggest charts with real data previews
03 Tabs Group views by business theme
04 Filters Finish with global controls

Copilot stays available through widgets, tabs and filters to refine the draft in natural language.

Step 1. Select a dataset

Datasets without description or semantic mapping stay visible, but disabled with guidance.

Revenue 360

Required: description + semantic mapping

Ready for AI
Finance Snapshot

Required: description + semantic mapping

Needs semantic context
People Ops Pulse

Required: description + semantic mapping

Needs semantic context
Step 2. Review suggested widgets

Keep, swap or deselect widgets before the builder is created.

✓
Revenue by channel bar_horizontal

Highlights the channels that drive growth.

✓
Monthly revenue trend line

Keeps the main temporal story in view.

✓
Top 5 sellers ranking

Shows who is pulling results forward.

Step 3. Organize the draft into tabs

AI groups widgets by business theme, not just by chart type.

Overview 4
  • KPIs
  • Trend
  • Margin
Performance 3
  • Share
  • Table
  • Margin
Rankings 2
  • Ranking
  • Table

Rename tabs and move widgets before publishing.

Step 4. Add global filters

The wizard suggests the controls most likely to be reused across the dashboard.

Period daterange
Region multiselect
Channel select
Sales rep search

Date range comes first. Then AI prioritizes high-usage categorical dimensions.

Mini-previews with real query data Auto layout ready for the builder Chat history lives in session state
WHY IT WORKS

The AI uses business context, not just field names

The draft becomes more useful because the model sees dataset descriptions, semantic tags and registry constraints before suggesting anything.

Dataset intent

The description explains what the dataset represents and what decisions it should support.

Semantic mapping

Measures, dimensions, dates and business tags guide which widgets are relevant and how they should be composed.

Registry-aware output

Suggested widgets stay aligned with the available widget types, slots and defaults already supported by the product.

Conversational refinement

The copilot keeps the draft editable through chat so teams can iterate before the builder opens.

TEAM IMPACT

What changes for the team

Less manual drag-and-drop to reach a credible first version.

Stronger consistency between business context and initial dashboard structure.

Faster collaboration between analysts, operators and decision makers.

A smoother bridge from AI suggestion to editable native dashboard.

Ready to scale your analytics?

Schedule a personalized demo and see how Scalar Analytics replaces your fragmented BI toolset with a single, intelligent platform.

Free technical assessment Personalized demo Privacy-ready environment Full data governance
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