Dataset opportunity
Ccpower — 维护日志数据集机会
Ccpower 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
73.4
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
获取
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 年的估值为 134 亿美元，预计复合年增长率为 23.2%。
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.
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
部分
Legal
混合所有权 — 易于许可
Buyer persona
工业人工智能与维护优化供应商
Ccpower 拥有一个高价值的维护日志数据集，采用时间序列模式，由其安装在各个客户现场的物理 UPS 和电池柜硬件生成。这些细粒度的iot_data捕获真实的运行指标和故障事件，使其非常适合训练和验证预测性维护人工智能模型，为工业资产性能提供了一个稀有的真相来源。
预测性维护的全球市场是该数据价值的明确指标，预计到 2025 年将达到134 亿美元，并以 23.2% 的复合年增长率增长。[1] 虽然访问需要导航客户服务协议，因为数据所有权共享，但聚合性能基准的专有性质使该数据集成为开发竞争性人工智能解决方案的独特且极有价值的资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据由安装在客户现场的物理硬件（UPS、电池柜）生成；细粒度遥测数据的拥有权可能与客户共享，但聚合性能基准很可能是专有的；访问需要导航有关远程监控数据的服务和维护协议。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证实 Ccpower 拥有其工业电源管理系统的专有历史维护日志和实时传感器数据。这个独特的数据集是开发预测性维护解决方案的人工智能供应商的关键资产，使他们能够训练预测设备故障和优化正常运行时间的模型。在一个预计将超过 134 亿美元的市场中，这种高稀有度的数据为改善资产性能和降低电信和数据中心最终用户的运营成本提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，工业部门，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 Demand95
人工智能买家需求异常高，这得益于预测性维护市场的快速增长，该市场正以 23.2% 的复合年增长率扩张。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License58
所有权=混合，许可=干净
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 Orientation22
0 个数据胃口信号（0 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 — 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. - ICP Audit92
✓ 良好目标 — 这家私营的电力系统制造商和维护服务提供商作为副产品生成有价值的运营数据（维护日志、系统性能），使其成为一个强有力的目标。问题：该公司为其自有硬件系统开发和销售监控软件（例如 Batt-Safe）。[10, 20] 这是一个临界案例，但软件的目的
- Deep Qualification70
✓ 通过 — C&C Power 制造和维护生成指定维护数据的电源监控硬件，使其成为数据持有者。然而，这些客户现场数据的拥有权和许可权尚未公开记录，代表着一个重大的未知数。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该公司从其电源监控产品中生成实时IoT 数据，捕获关键的运行指标，如电压、电流和温度，这些是训练异常检测模型的基础。
Industrial data
Ccpower 从其工业电源解决方案中捕获性能数据，提供系统级别的电力流和效率指标，这对于理解整体资产健康状况至关重要。
Maintenance logs
该数据集包括详细说明系统正常运行时间和事件的历史维护日志，提供了训练和验证高价值工业资产预测性故障模型所需的关键地面真实标签。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Ccpower 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 $13.4 billion in 2025, with a projected CAGR of 23.2% (source: Polaris Market Research). [1]. Investment score 73.4/100 (confidence 0.49). Recommended action: Acquire.
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