Reported impact
Business outcome
Efficient control with Microsoft Fabric optimizes hydrogen production at OGE
- Cost Reduction
- Productivity Improvement
MicrosoftEnergyData Lake / Data Warehouse ModernizationReal-time AnalyticsAI and Machine LearningCloud MigrationData AnalyticsData PlatformCost ReductionProductivity Improvement2025 MicrosoftMS#0078d4EnergyGermanySo far, this has been a challenge.We can bring down production costs by around 50 percent just through economic optimization based on machine…Jan 13, 20255Data Lake / Data Warehouse Modernization|Real-time AnalyticsAzure Machine Learning · Microsoft Fabric0 2025-01-13 5
Open Grid Europe GmbH
Data Lake / Data Warehouse Modernization · Real-time Analytics
So far, this has been a challenge.
We can bring down production costs by around 50 percent just through economic optimization based on machine learning.
Solution
Open Grid Europe GmbH, a Energy organization in Germany, modernized this real-time analytics workload with Microsoft Fabric, and Azure Machine Learning. So far, this has been a challenge. Microsoft Fabric unifies data engineering, storage, analytics, and BI on a shared data platform. Azure Machine Learning trains, manages, and deploys machine learning models used in the production workflow. Data from operational systems is ingested into Microsoft Fabric, processed across Azure Machine Learning, and surfaced through Azure Machine Learning so teams can act on fresher operational insight. Uses a shared Microsoft Fabric data foundation for analytics and reporting workloads. Efficient control with Microsoft Fabric optimizes hydrogen production at OGE.
Data flow
Data from operational systems is ingested into Microsoft Fabric, processed across Azure Machine Learning, and surfaced through Azure Machine Learning so teams can act on fresher operational insight.
Solution architecture
- Compute
- Azure Machine Learning trains, manages, and deploys machine learning models used in the production workflow.
- Storage
- Microsoft Fabric unifies data engineering, storage, analytics, and BI on a shared data platform.
Architecture clues
- Uses a shared Microsoft Fabric data foundation for analytics and reporting workloads.
Evidence from the source
Efficient control with Microsoft Fabric optimizes hydrogen production at OGE
OGE therefore uses the Microsoft Fabric digitalization platform to present hydrogen production as a digital twin. Real-time production data is analyzed in order to make data-based decisions for operations.
So far, this has been a challenge.
The platform links real-time electricity prices with internal data and calculates the expected price for 1 kg of H₂. This allows the production plan to be optimized. This reduces manufacturing costs by up to 50%.
were also integrated into the platform. And this has had a significant impact, as Marcus Rübsam, Managing Director of CibusCell Technology, explains: “We can bring down production costs by around 50% just through economic optimization based on machine learning.”
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
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 value57/100
- Problem clarity5/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity12/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact15/251 metric describe measurable impact.
- Deployment scale5/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity8/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.microsoft.com/en/customers/story/20135-open-grid-europe-gmbh-azure-marketplaceMicrosoftFirst-party
Open Grid Europe GmbH 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
- Publication date
Date evidence
- Published on source page Jan 13, 2025 · Microsoft · First-partyOpen 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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