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Databricks Manufacturing United States

Corning

Enterprise Knowledge Search · Real-time Analytics

Corning collects data from hundreds of sources globally, and new sources emerge almost daily. The company’s legacy data warehousing solution could no longer keep pace, and analytics activities were cumbersome.

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2,500 Jobs running
900 Active Databricks users
~5 petabytes Data unified by Databricks
“To accomplish all that over 400 different datasets with different teams was a big challenge,” said Hamenoo.

Reported impact

Business outcome

Reported outcomes include ~5 petabytes Data unified by Databricks; 2,500 Jobs running; 900 Active Databricks users.

  • Compliance
  • Cost Reduction
  • Productivity Improvement

Solution

Corning built its Databricks implementation around Lakeflow Jobs, More from, Databricks Data + AI Platform, Databricks Assistant. Corning collects data from hundreds of sources globally, and new sources emerge almost daily. The company’s legacy data warehousing solution could no longer keep pace, and analytics activities were cumbersome. Lakeflow Jobs schedules and orchestrates recurring data pipelines and transformations. More from more from is part of the named implementation described in the customer story. Databricks Data + AI Platform provides the shared lakehouse environment for ingestion, engineering, analytics, and AI workflows in this deployment. Databricks Assistant helps practitioners accelerate code, query, and troubleshooting work inside the Databricks workspace. The solution also connects to Power BI, BigQuery, Airflow, so teams can work from a shared governed environment instead of disconnected tools.

Data flow

Source data is ingested into databricks, curated in shared lakehouse tables, processed with Databricks compute and orchestration services, and exposed to downstream analytics and users. It connects with Power BI, BigQuery, Airflow.

Solution architecture

6 components · 5 layers
  1. Ingest
    • Lakehouse Federation Lets teams query remote systems alongside lakehouse data without copying all source data first.
  2. Serving
    • Databricks Assistant Helps practitioners accelerate code, query, and troubleshooting work inside the Databricks workspace.
  3. Orchestration
    • Lakeflow Jobs Schedules and orchestrates recurring data pipelines and transformations.
  4. Governance
    • Unity Catalog Applies centralized governance, lineage, auditing, and access control across shared data assets.
  5. Uncategorized
    • More from More from is part of the named implementation described in the customer story.
    • Databricks Data + AI Platform Provides the shared lakehouse environment for ingestion, engineering, analytics, and AI workflows in this deployment.

Architecture clues

  • Databricks Assistant
  • Databricks Data + AI Platform
  • Lakeflow Jobs
  • More from
  • medallion architecture
  • serverless

Evidence from the source

2,500 Jobs running
Corning turned to the Databricks Data + AI Platform to centralize their data sources. “Databricks allows us to bring all our data into the platform in all different formats,” shared Hamenoo.
Corning uses Databricks Lakeflow Jobs to execute multiple data pipeline tasks, enabling full medallion pipeline orchestration. Raw data ingested from various sources is brought into a Bronze layer.
Jibreal Hamenoo, Principal System Engineer, Data Engineering at Corning, wanted to create a central data source to enable data engineers, machine learning engineers and data scientists to self-serve. Ultimately, this would help Corning achi
The Data + AI Platform also provides Corning the compute power they need to derive insights faster. “Instead of a data scientist loading data locally into a client, they can go into the Databricks workspace, stand up an instance of the righ
~5 petabytes Data unified by Databricks
Transparency Evidence & methodology 96/100 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 value96/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    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
    6 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

    Corning customer story

    First-party
    https://www.databricks.com/customers/corning
    Source type
    Vendor-published customer story
    Published
    Jul 29, 2024
    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. Human Rights Campaign

    Corning Incorporated - HRC

    Independent secondary
    https://www.hrc.org/resources/corporations/corning-incorporated

    The employer profile lists Headquarters as "Corning, NY" and Address as "1 Riverfront Plaza, Corning, NY 14831," supporting a United States headquarters country.

    Source type
    Structured company profile
    Supports
    • Region

Date evidence

  • Published on source page Jul 29, 2024 · Databricks · First-party
    Open date source
Not separately sourced Industry, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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