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Google Cloud Travel and Hospitality United States

Thrive Restaurant Group

Data Lake / Data Warehouse Modernization · Document Processing · Real-time Analytics

However, rapid growth through acquisitions created a complex technological environment. With nearly 30 disparate systems and more than 200 restaurants across various time zones, teams were spending more time manually extracting data from various silos rather than focusing on the guest experience.

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Accelerated time to insights from three hours to 30 seconds with LookML
Began unifying 30+ disparate systems into one with Gemini Enterprise
Cut data integration time by 50% with BigQuery
Reduced monthly financial reporting hours by approximately 10%

Reported impact

Business outcome

Began unifying 30+ disparate systems into one with Gemini Enterprise; Cut data integration time by 50% with BigQuery; Reduced monthly financial reporting hours by approximately 10%; Reduced time to produce P&Ls from 8+ hours to under 50 minutes monthly.

  • Productivity Improvement
  • Revenue Growth

Solution

To solve these fragmentation issues, Thrive is cultivating a modern data stack centered on and Looker . Using automated connectors like Airbyte, the team moved data from isolated APIs into a central BigQuery warehouse, with a goal of reducing data integration times by 50%. Thrive is using BigQuery and Gemini with the goal of cutting data integration time by 50% to help restaurant managers focus more on customer and team experiences. Building on this foundation, Thrive is now working with Cobry to deploy to turn complex technology into a clear operational advantage. While data traditionally shows what happened in a restaurant, Cobry demonstrated how Gemini Enterprise could explain the reason behind it by unifying BigQuery data with Google Workspace emails and documents. Now, instead of just seeing a sales variance, a manager can ask the system for context, surfacing historical details—like a past equipment failure or local event—that would otherwise remain a mystery.

Data flow

stored or unified in BigQuery, and surfaced through Gemini Enterprise, Gemini, Looker

Solution architecture

5 components · 3 layers
  1. Storage
    • BigQuery Stores and queries the analytics and AI-ready datasets that power the workload.
  2. Serving
    • Gemini Enterprise Provides a secure enterprise environment for teams to use Gemini with governed data access.
    • Gemini Powers natural-language reasoning, summarization, generation, or assistance inside the workflow.
    • Looker Provides the governed semantic layer, dashboards, and self-service analytics used by business teams.
  3. Governance
    • LookML Defines governed metrics and semantic models so teams and AI workflows use the same business logic.

Architecture clues

  • # Thrive puts humans at the forefront of restaurant operations with Gemini Enterprise
  • Accelerated time to insights from three hours to 30 seconds with LookML
  • Began unifying 30+ disparate systems into one with Gemini Enterprise
  • BigQuery and Looker
  • Cut data integration time by 50% with BigQuery
  • Thrive is using BigQuery and Gemini with the goal of cutting data integration time by 50% to help restaurant managers focus more on customer and team experiences.

Evidence from the source

Accelerated time to insights from three hours to 30 seconds with LookML
Began unifying 30+ disparate systems into one with Gemini Enterprise
Cut data integration time by 50% with BigQuery
Reduced monthly financial reporting hours by approximately 10%
Reduced time to produce P&Ls from 8+ hours to under 50 minutes monthly
Transparency Evidence & methodology 90/100 reference value · 82% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    6 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence82%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency9/10
    2 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Google Cloud

    Thrive Restaurant Group customer story

    First-party
    https://cloud.google.com/customers/thrive-restaurant-group
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
  2. Thrive Restaurant Group

    Thrive Restaurant Group

    First-party
    https://www.thriverestaurantgroup.com/

    The Organization schema lists streetAddress '1877 N Rock Road', addressLocality 'Wichita', addressCountry 'US', and numberOfEmployees value 8000.

    Source type
    Official company website
    Supports
    • Company size

Date evidence

  • First archived Apr 28, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jul 30, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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