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Snowflake Education Tallahassee, Florida

Florida State University

Real-time Analytics

connect dozens of university data sources, shorten time to deliver new data products, and unlock value from unstructured documents for research and operations.

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11x Increase in connected data sources — while accelerating performance
95% Faster time to value for internal stakeholders, sharing data in five days vs. 90 previously

Reported impact

Business outcome

Florida State University achieved 95% Faster time to value for internal stakeholders, sharing data in five days vs. 90 previously and 11x Increase in connected data sources — while accelerating performance.

  • Productivity Improvement

Solution

Florida State University uses Snowflake, Document AI, Secure Data Sharing, and Horizon Catalog on Snowflake to connect dozens of university data sources, shorten time to deliver new data products, and unlock value from unstructured documents for research and operations. Student, academic, operational, and document data are centralized in Snowflake so analysts, operators, and business teams can work from a faster, more reliable operating view. Document AI extends the platform beyond structured tables by extracting useful fields from PDFs and other unstructured content. Keeping ingestion, storage, transformation, and governed access on one platform reduces handoffs, simplifies operations, and makes it easier to reuse trusted data across analytics, reporting, and AI. Florida State University achieved 95% Faster time to value for internal stakeholders, sharing data in five days vs. 90 previously and 11x Increase in connected data sources — while accelerating performance.

Data flow

student, academic, operational, and document data flow into Snowflake, Document AI, Secure Data Sharing, and Horizon Catalog; curated data, reports, and model outputs are then served to analysts, operators, and business teams.

Solution architecture

4 components · 4 layers
  1. Compute
    • Document AI Extracts structured values from unstructured documents inside Snowflake.
  2. Storage
    • Snowflake Provides the centralized data platform that stores governed datasets and serves analytics or AI workloads.
  3. Serving
    • Secure Data Sharing Shares governed data with partners or internal consumers without moving copies.
  4. Governance
    • Horizon Catalog Applies cataloging, governance, and policy controls across Snowflake data assets.

Architecture clues

  • Document AI extends the platform beyond structured tables by extracting useful fields from PDFs and other unstructured content.
  • Horizon Catalog adds cataloging, governance, and policy controls that make broader data access safer to operate at scale.
  • Operates at the scale described by metrics such as 95% Faster time to value for internal stakeholders, sharing data in five days vs. 90 previously.
  • Secure Data Sharing lets the organization collaborate with partners or downstream consumers on live governed data without creating extra copies.

Evidence from the source

11x Increase in connected data sources — while accelerating performance
95% Faster time to value for internal stakeholders, sharing data in five days vs. 90 previously
But the university’s previous data architecture was difficult to scale and maintain
Florida State University achieved 95% Faster time to value for internal stakeholders, sharing data in five days vs. 90 previously and 11x Increase in connected data sources — while accelerating performance
With Snowflake, Florida State University combines data from 47 disparate sources, responds 95% faster to stakeholders’ data needs, maximizes value from unstructured data and delivers a better student experience
Transparency Evidence & methodology 95/100 reference value · 79% confidence · 1 source

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 value95/100
  • 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
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 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 transparency8/10
    1 source reference 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. Snowflake

    Florida State University customer story

    First-party
    https://www.snowflake.com/en/customers/all-customers/case-study/florida-state-university/
    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

Date evidence

  • First archived Nov 11, 2024 · 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 Jan 23, 2026 · Snowflake · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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