Dataset opportunity
Solareur — 维护日志数据集机会
Solareur 持有的中等维护日志数据集，可用于预测性维护和异常检测。
Score
71.9
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
49%
Action
收购
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market size (indicative estimate)
全球预测性维护市场在 2025 年的价值为 136.5 亿美元，预计复合年增长率为 24.30%（来源：Fortune Business Insights）。[4]
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
Solareur 持有的时间序列 维护日志数据集源于其作为第三方太阳能资产的 EPC 合作伙伴的角色。该数据集包含来自运行硬件的精细化 `industrial_data` 和 `iot_data` 流，提供了训练强大预测性维护人工智能模型所需的高保真、真实世界记录。
业务价值目标是全球预测性维护市场，这是一个有价值的领域，估计在 2025 年将达到136.5 亿美元，预计复合年增长率为 24.30%。[4] 虽然聚合和匿名化此客户数据的权利需要 O&M 合同的验证，但 Solareur 作为 EPC 合作伙伴直接访问硬件和数据流确保了数据的完整性。这为获取高质量的iot_data以用于这一高增长应用提供了难得的机会，证明了尽职调查的合理性。⚠ 尽职调查（有价值的数据，可协商的访问权）：数据来自第三方客户（中小企业和投资者）拥有的太阳能资产；聚合和匿名化监控数据以进行人工智能训练的权利必须在 O&M 合同中进行验证；公司作为 EPC 合作伙伴运营，这意味着他们可以直接访问硬件和数据流 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Solareur 拥有专有的、稀有度高的数据集，该数据集结合了详细的维护日志和来自其工业太阳能园区的实时物联网数据。这种独特的时间序列数据是工业人工智能供应商开发预测性维护解决方案的关键资产。在一个预计年增长率超过 24% 的市场中，该数据集为在经历大规模扩张的可再生能源运营领域训练和验证算法提供了难得的机会。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，工业领域，3 种特定类型
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 个证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
适用于预测性维护
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
人工智能买家需求极高，这得益于预测性维护市场的快速增长，该市场正以 24.30% 的复合年增长率扩张。[4]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility30
中等难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 种证据类型，3 个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
所有权=混合，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation56
2 个数据需求信号（2 种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
盈余=高，5 个近期外部信号 — 专有数据超出已货币化的部分
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset.
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>Initialement concentrée sur la prospection foncière pour les développeurs solaires, la plateforme Ferme Solaire change de nom à l’occasion d’une diversification. Elle s’appellera désormais Solmeria et va  </p> <p>L’article <a href="https://www.greenunivers.com/2026/07/solmeria-ex-ferme-solaire-veut-proposer-des-projets-enr-a-lunite-428542/">Solmeria (ex Ferme Solaire) veut proposer des projets EnR à l’unité</a> est apparu en premier sur <a href="https://www.greenunivers.com">GreenUnivers</a>.</p>”
- “<p>Les représentants du personnel d’Urbasolar montent au créneau. Dans un communiqué publié hier, les membres du comité social et économique (CSE), portés par le syndicat des cadres CFE-CGC critiquent les mesures proposées par la direction qu’ils jugent « dérisoires » au regard des revenus et de la trésorerie du propriétaire du développeur-producteur photovoltaïque de Montpellier, l’énergéticien suisse Axpo. […]</p> <p>L’article <a href="https://www.greenunivers.com/2026/07/les-representants-syndicaux-durbasolar-prets-a-la-greve-428482/">Les représentants syndicaux d’Urbasolar”
- “<p>Chaque semaine, GreenUnivers sélectionne les principaux événements professionnels de la transition énergétique. Des rendez-vous qui ont lieu en France et ailleurs dans les secteurs des énergies renouvelables, de l’hydrogène, de la rénovation ou encore de la mobilité électrique. Août 26 La Ref, les Rencontres des entrepreneurs de France, Medef, Paris 28 Universités d’été de l’économie […]</p> <p>L’article <a href="https://www.greenunivers.com/2026/07/lagenda-de-la-transition-energetique-280-424554/">L’agenda de la transition énergétique</a> est apparu en premier sur <”
IoT / sensor data
该公司通过对太阳能设备性能进行实时监控生成时间序列数据，这对于训练模型以检测异常和优化能源生产至关重要。
Maintenance logs
Solareur 根据技术人员关于现场干预的报告创建结构化的维护日志，提供标记预测模型故障事件所需的关键地面实况数据。
Industrial data
这些证据证实了数据源自大型工业规模的太阳能园区建设和运营，确保了其复杂性和对强大人工智能应用的相关性。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
JSON, CSV
License
One-time license for use in predictive maintenance AI model training and development. Rights to aggregate and anonymize client data require verification in O&M contracts.
Personal data
No PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset is highly valuable due to its rarity as proprietary, real-time time-series maintenance and IoT data from solar assets, directly feeding the high-growth global predictive maintenance market. Its granular nature is critical for training robust AI models in a sector projected for significant expansion.
Detailed schema & sample available on access request.
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This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Solareur Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market was valued at $13.65 billion in 2025 and is projected to grow at a CAGR of 24.30% (source: Fortune Business Insights). [4]. Investment score 71.9/100 (confidence 0.49). Recommended action: Acquire.
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