Brainforge Knowledge

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Eden Omni Stakeholder Training — Slides Outline (45 min)

Design guidance:

  • Minimal text; screenshots/gifs where possible during delivery
  • Pricing: conceptual (seat strategy + tokens), no dollar amounts

Slide 1 — Title

Eden Analytics in Omni
Dashboards, Topics, AI, and operational workflows

Speaker notes:

  • Mixed audience; we’ll split hands-on paths at the end.

Slide 2 — Outcomes

  • Find familiar dashboards
  • Filter/drill/export confidently
  • Understand Topics (semantic layer)
  • Use AI safely (if enabled)
  • Replace screenshots with deliveries/alerts

Slide 3 — What’s changing (Tableau → Omni)

  • Same business questions
  • Faster iteration + governed self-serve
  • AI-assisted exploration (with guardrails)

Slide 4 — Users & roles (seat types; no numbers)

Developer: models, connections, permissions
Standard: create charts/dashboards + AI + context
Viewer: explore + export + schedule + alerts

Speaker notes:

  • Most stakeholders = Viewer; small number = Standard; very few = Developer.

Slide 5 — Seat strategy (how to keep cost sane)

  • Start with a lean Standard group
  • Use deliveries to distribute widely
  • Expand seats only when there’s real self-serve demand

Slide 6 — AI strategy (entitlement + budget)

  • Not everyone needs AI-enabled access
  • Tokens are a shared monthly budget (don’t roll over)

Speaker notes:

  • AI quality depends on Topic definitions and context.

Slide 7 — “Daily driver” dashboards (what we migrate first)

Examples:

  • Unit Economics / Profitability
  • Order Journey / SLA / pharmacy turnaround
  • Retention / marketing cohorts

Speaker notes:

  • Ask: “Which dashboard do you use daily?”

Slide 8 — Demo: navigation + filters

Checklist:

  • Find the dashboard
  • Change date range
  • Change one business filter

Slide 9 — Demo: export patterns

  • Export/download CSV for row-level work
  • PDF for executive snapshot workflows

Slide 10 — Topics (semantic layer) in plain English

Topic = approved dataset for a set of questions

  • joins
  • definitions/assumptions (grain, inclusion rules)
  • governance

Slide 11 — How dashboards compose

  • A dashboard can contain charts from multiple Topics
  • Each chart points to one Topic

Slide 12 — Consistent definitions (Eden rule)

  • Keep core definitions consistent across Topics
  • Avoid “finance revenue” vs “marketing revenue” conflicts

Slide 13 — AI: what it’s good at

  • Exploration and summarization
  • Drafting charts/questions
  • Faster “first pass” analysis

Slide 14 — AI: guardrails

Always validate:

  • timeframe (partial days?)
  • grain (order vs transaction vs customer)
  • filters (paid/pending/cancelled)

Slide 15 — Mobile view

  • Use mobile for quick KPI checks
  • Ensure key tiles are readable

Slide 16 — Turning snapshots into a workflow (the big win)

Replace:

  • screenshots + manual Slack posts
    With:
  • scheduled PDF/CSV deliveries + alerts

Slide 17 — Hands-on (split path)

Everyone: open dashboard → change filters → export
Viewers: draft a delivery/alert
Builders: create one chart → save to a Training dashboard

Slide 18 — Close

  • Decide seat mix + AI access plan
  • Identify 1 daily snapshot to convert to a delivery
  • Identify top 3 Topics needed for P0 dashboards and AI usefulness

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