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Databricks Manufacturing Global

Red Hat

Document Processing · Marketing Personalization · Real-time Analytics

But even in a highly data-driven marketing organization, teams trying to answer performance questions and find insights were slowed by fragmented information across dashboards, documents, spreadsheets and internal tools.

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$1.3M In annual productivity value
70% Faster time-to-insight for marketers
After running 20 focus groups, the team identified common pain points around dashboard navigation, metric definitions, campaign analysis, and frequently asked questions.
Approximately 34,000 Hours saved annually

Reported impact

Business outcome

Red Hat achieved measurable business impact on Databricks, including 70% Faster time-to-insight for marketers; Approximately 34,000 Hours saved annually; $1.3M In annual productivity value.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Red Hat is the world’s leading provider of enterprise open source software solutions, helping organizations, including 90% of the Fortune 500, run mission-critical workloads across hybrid cloud, automation, Linux and beyond. But even in a highly data-driven marketing organization, teams trying to answer performance questions and find insights were slowed by fragmented information across dashboards, documents, spreadsheets and internal tools. To solve this, Red Hat built the Marketing Insights and Navigation Engine (MINE) . Powered by an open hybrid cloud foundation ( Red Hat OpenShift ) and integrating Databricks for advanced data engineering and data management, MINE is a marketing intelligence platform that gives marketers seamless access to trusted answers, enabling them to navigate performance data and move from insight to action faster.

Data flow

Unstructured documents and reference data lands in Databricks and is transformed into curated datasets

Solution architecture

1 components · 1 layer
  1. Compute
    • Agent Bricks Supports agentic or GenAI applications that Red Hat uses to automate or accelerate work.

Architecture clues

  • Cloud: AWS
  • Key product: Agent Bricks
  • Real-time or streaming data processing

Evidence from the source

$1.3M In annual productivity value
70% Faster time-to-insight for marketers
After running 20 focus groups, the team identified common pain points around dashboard navigation, metric definitions, campaign analysis, and frequently asked questions.
Approximately 34,000 Hours saved annually
Red Hat is the world’s leading provider of enterprise open source software solutions, helping organizations, including 90% of the Fortune 500, run mission-critical workloads across hybrid cloud, automation, Linux and beyond.
Transparency Evidence & methodology 85/100 reference value · 92% 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 value85/100
  • 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
    3 metrics describe measurable impact.
  • Deployment scale0/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence92%
  • 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 provenance10/10
    The publication date comes from the source page or publisher.
  • 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. Databricks

    Red Hat customer story

    First-party
    https://www.databricks.com/customers/red-hat
    Source type
    Vendor-published customer story
    Published
    Jun 4, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date
  2. LeadIQ

    Red Hat Employee Directory, Headcount & Staff | LeadIQ

    Independent secondary
    https://leadiq.com/c/red-hat/5a1d8aa424000024006481f1/employee-directory

    The page's Organization JSON-LD lists numberOfEmployees value 19535, and the visible page text says Red Hat has approximately 20K employees as of August 2026.

    Source type
    Structured company profile
    Supports
    • Company size

Date evidence

  • Published on source page Jun 4, 2026 · Databricks · First-party
    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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