Reported impact
Business outcome
Reported outcomes include 650 Users including data engineers, scientists, analysts, stewards and viewers; 100 Reports and dashboards running on Databricks; 60 Use cases implemented on Databricks.
DatabricksEnergyMarketing PersonalizationSupply Chain OptimizationAI and Machine LearningCloud MigrationData Platform2025 DatabricksDB#ff3621EnergyEuropeThe organization needed a more developed data management platform for their on-premises legacy environment.100 Reports and dashboards running on DatabricksMar 5, 20256Marketing Personalization|Supply Chain OptimizationDatabricks Data + AI Platform · Databricks SQL · Delta Lake0 2025-03-05 6
Plenitude
Marketing Personalization · Supply Chain Optimization
The organization needed a more developed data management platform for their on-premises legacy environment.
100 Reports and dashboards running on Databricks
60 Use cases implemented on Databricks
650 Users including data engineers, scientists, analysts, stewards and viewers
Solution
Plenitude is a company owned by Eni that integrates production from renewables, energy sales, energy services and a large network of electric vehicle charging points. Plenitude leverages data and AI for optimized efficiency organizationwide. Migrating to the Databricks Data + AI Platform on the cloud, the company expanded data usage, enhancing operational efficiency and customer engagement through demand forecasting, segmentation and personalization. Paolo Maltese, Data & AI Platform Product Owner at Plenitude, explained, “The challenges around managing various data sources and types impacted our ability to enable downstream analytics for BI, SQL and ML for various data teams and stakeholders in terms of data product time to market, skill diffusion for data analysis and understanding, data quality and trust.
Data flow
Customer, product, and engagement data lands in Databricks, is transformed in Delta Lake tables under Unity Catalog governance, and is served to downstream users and applications through Databricks SQL, Delta Sharing.
Solution architecture
- Compute
- Databricks Data + AI Platform Provides the shared lakehouse environment for ingestion, engineering, analytics, and AI workloads.
- Storage
- Delta Lake Stores curated lakehouse tables used for reliable downstream analytics and AI workloads.
- Serving
- Databricks SQL Serves dashboards, self-service queries, and business intelligence for downstream users.
- Delta Sharing Delivers governed data access across agencies, partners, or business units without copying datasets.
- Governance
- Unity Catalog Applies centralized governance, lineage, and access controls across shared data assets.
Architecture clues
- Uses Delta Sharing for governed data access across teams or partners.
- Uses Unity Catalog for centralized governance and access control.
Evidence from the source
100 Reports and dashboards running on Databricks
60 Use cases implemented on Databricks
650 Users including data engineers, scientists, analysts, stewards and viewers
Plenitude is a company owned by Eni that integrates production from renewables, energy sales, energy services and a large network of electric vehicle charging points.
Plenitude leverages data and AI for optimized efficiency organizationwide.
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 value87/100
- Problem clarity20/20Measures 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 impact25/253 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
- 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 specificity10/10Rewards 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.databricks.com/customers/plenitudeDatabricksFirst-party
Plenitude 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 Mar 5, 2025 · Databricks · 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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