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Analytics & Reporting Dashboards

Decision-grade analytics for operators — not vanity dashboards for boards.

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The problem

Most dashboards exist to make boards feel informed. Operator dashboards exist to change a decision in the next hour. The two should not look alike, and most products confuse them.

How we approach it

  1. 01Start from the decision being made, not the data being available.
  2. 02One number per screen, with the next decision implied by the layout.
  3. 03Drill-down only when the headline number demands it.
  4. 04Alerting on thresholds, not on dashboards.

Capabilities

  • Operator dashboards (front desk, dispatch, fulfillment, support)
  • Executive dashboards (revenue, margin, occupancy, retention)
  • Cohort and retention analytics
  • Custom data warehouses (BigQuery, Snowflake, Postgres+dbt)
  • Embedded analytics for SaaS products
Stack
  • dbt for transformation, Postgres or BigQuery for storage
  • Cube / Metabase / Evidence / custom React for the UI layer
  • Airbyte / Fivetran / custom connectors for ingestion
Deliverables
  • Production data warehouse with tested models
  • Dashboards designed against named decisions
  • Alerting wired to operational channels
  • Documentation of metrics, definitions, and lineage
Fit for
  • Operators whose decision quality is bottlenecked by data access
  • SaaS products needing customer-facing analytics
Not for
  • 'Make us a dashboard' with no decision named

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