One Pane of Glass Across 15 Restaurants

Unifying Toast POS, Yelp, UKG, and manual feedback into a real-time analytics platform on GCP.

Overview.

A fast-growing US restaurant group operating 15+ locations across full-service and fine-casual brands. Operations, labor, and guest-experience teams were buried in fragmented data — Toast POS, Yelp reviews, UKG workforce, and manual Excel feedback — none of it talking to each other.

TECH STACK

Google Cloud Platform · GCP Data Lake · BigQuery (curated data marts, semantic layer) · Power BI (4 role-specific dashboards) · Toast POS · Yelp · UKG Workforce · Excel ingestion

The Challenge.

Growth had outpaced visibility. Each new location added more data and less clarity. Operators couldn’t compare locations on a like-for-like basis, and labor and inventory issues only surfaced after they hurt the P&L.

  • Fragmented data: Toast POS sales, Toast inventory, UKG schedules, and Yelp reviews lived in four disconnected silos; no unified view of any single location, let alone the chain.
  • No real-time visibility: Labor cost, kitchen wait times, and guest satisfaction were reported days after the fact, if at all.
  • Inventory blind spots: Toast out-of-stocks went unnoticed for hours; menu gaps lingered; replenishment was reactive, not proactive.
  • Manual workforce reconciliation: UKG schedules vs. punches reconciled by hand, after payroll — with predictable errors.

Our Solution.

Pegasus One built an end-to-end data platform on Google Cloud — ingesting Toast, Yelp, UKG, and Excel sources into a unified data lake, transforming them in BigQuery, and exposing curated KPIs through four role-specific Power BI dashboards. Operators, labor leaders, and guest-experience teams now share one version of the truth, refreshed continuously.

  • Unified GCP Data Lake: Ingests Toast POS (sales, orders, inventory, schedules), Yelp (ratings, reviews), UKG (workforce, payroll, labor hours), and manual Excel feedback into a single landing zone.
  • BigQuery warehouse + semantic layer: Curated data marts and a Power BI semantic layer deliver consistent, governed metrics across every dashboard.
  • Toast Operations Heat Map: Daily sales and covers, kitchen wait times, seat delay by hour, table utilization, and covers per seat-hour.
  • Service Coordinator dashboard: Yelp / Google 5★ percentage, waitlist quote accuracy, and compensation tracking in one place.
  • Toast Inventory + UKG Workforce dashboards: Out-of-stock items, OOS duration, menu gaps, and replenishment speed; plus master schedule, scheduled-vs-actual, and schedule-vs-punch variance.

ARCHITECTURE.

Toast POS · Yelp · UKG · Excel → GCP Data Lake → BigQuery transformations → Curated data marts → Power BI semantic layer → 4 role-specific dashboards (Operations, Service, Inventory, Workforce).

Results.

 

15+
Locations unified
4
Role-based dashboards
4
Source systems integrated
Real-time
Operational visibility