Dataset opportunity
E Installation — 维护日志数据集机会
E Installation 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
66.7
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 = 2024 年为 109.3 亿美元，复合年增长率为 26.5%。
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-07-27
Elektroservice Brügmann GmbH — Germany – Building construction work – Sanierung Rathaus 2. BA
ted.europa.eu ↗
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.
- ✨Signal
专注于通信和数据网络的安装
source ↗
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
定期
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — 许可权待明确
Buyer persona
工业人工智能与维护优化供应商
E Installation 持有一个有价值的时间序列数据集，其中包含超过 600 个工业和住宅单元的维护日志和检查记录。这些历史数据经过结构化处理，可用于训练预测性维护模型，从而在设备发生故障之前准确预测故障并优化维护计划。
该数据的商业价值体现在全球预测性维护市场，该市场在 2024 年的估值为109.3 亿美元，预计将以 26.5% 的复合年增长率增长。[5] 虽然访问此专有数据需要对住宅记录进行 GDPR 合规性审查，但其作为区域中小型企业真实世界数据集的稀有性，为在快速扩张的市场中开发和验证强大的 AI 解决方案提供了独特的优势。⚠ 合规性审查（有价值的数据，可协商访问）：区域中小型企业，可能拥有手动或基本数字记录；数据包括 600 多个住宅单元和工业场所的维护历史；技术数据是专有的，但如果与特定住宅地址相关联，可能需要进行 GDPR 合规性审查 · 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 E Installation 拥有来自各种工业、农业和基础设施资产的专有维护日志数据集。这些数据直接服务于高增长的预测性维护市场，该市场价值超过 109 亿美元并正在迅速扩张。对于工业人工智能供应商而言，这种独特的时间序列数据对于训练和验证优化资产性能、预测故障和减少运营停机时间的算法至关重要，使其成为一项稀有且有价值的资产。
See dimension details ↓- Dataset Specificity90
主导的 'maintenance_logs'，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 Freshness46
定期
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
人工智能买家需求旺盛，这得益于预测性维护市场的快速扩张，该市场正以 26.5% 的复合年增长率增长。[5]
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 Feasibility44
低难度，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 License70
所有权=公司所有，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 Orientation39
1 个数据需求信号（1 种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus42
盈余=低，1 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. - ICP Audit100
✓ 良好目标 — 这家荷兰电气安装和维护公司是理想的中小型企业目标，因为其核心业务会产生有价值的维护日志作为副产品，并且似乎不销售数据或情报。问题：该公司已被收购，现为母公司 Constructif 的运营子公司，这可能会使决策过程复杂化。
- Deep Qualification70
✓ 通过 — 该目标是维护日志的合理数据持有者，但初步提示错误地识别了公司的名称。数据所有权和许可权是重大的未知障碍，由于存在住宅客户数据，GDPR 敏感性是一个明确的因素。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Maintenance logs
这些证据证实该公司通过服务于多样化的工业和农业运营组合，生成时间序列维护日志，提供了训练预测性故障模型所需的原始历史数据。
Inspection reports
这些文件详细说明了设备检查和电气系统安装，提供了关键的地面实况数据，通过具体的资产状况信息丰富了时间序列日志。
Industrial data
这些时间序列数据展示了维护光伏和移动通信系统等现代基础设施资产的历史记录，这是性能优化算法的一个高价值领域。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Coverage
Scanned sources
Deliverable
Premium dataset report
E Installation 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 = $10.93B in 2024, CAGR 26.5% (source: Fortune Business Insights). [5]. Investment score 66.7/100 (confidence 0.49). Recommended action: Acquire.
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