Dataset opportunity
Smegroup — 维护日志数据集机会
Smegroup 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
68.6
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 = 2023 年为 67.6 亿美元，复合年增长率为 27.4%。
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.
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
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
Smegroup 持有大量的维护日志，格式为时间序列，这些日志收集自其在医疗、能源和机械工程领域的多元化工业采购和运营活动。这些细粒度的 `industrial_data` 为开发和训练高精度预测性维护模型提供了直接而强大的基础，捕捉了设备随时间的实际性能和故障事件。
商业价值巨大，因为全球预测性维护市场在 2023 年的估值为67.6 亿美元，预计将以 27.4% 的复合年增长率扩张。[9] 尽管由于三方客户-供应商关系和数据保密条款存在访问复杂性，但这些 `procurement` 和 `maintenance_logs` 的固有稀缺性和已证实的适用性使其成为寻求在此高增长市场中创造价值的 AI 买家的优质资产。[9] ⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据涉及 SME Group、工业客户和供应商之间的三方关系；采购外包合同中的保密条款可能限制数据共享；数据可能分散在不同的工业领域（医疗、能源、机械工程）中。· 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 Smegroup 拥有记录工业运营和维护日志的专有时间序列数据。这正是 AI 供应商为构建和训练预测性维护模型所寻求的稀缺、高价值资产类型。该数据集的价值因其涵盖了从机械工程到能源等多元化高价值领域而得到提升，在一个预计复合年增长率为 27.4% 的市场中，这使其成为一个及时且具有战略意义的机会。
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 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 Demand95
AI 买家需求异常高，这得益于市场从 67.6 亿美元以 27.4% 的复合年增长率快速增长，因为公司竞相采用数据驱动的维护解决方案以降低运营成本和停机时间。[9]
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 次命中
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 Orientation22
0 数据需求信号（0 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 Audit100
✓ 良好目标 — Smegroup 是一个理想的目标，作为一家德国中小型企业，提供工业采购和物流服务，这些服务产生了专有的供应链和运营数据作为副产品，并且不将其作为核心产品出售。[3, 7] 问题：公司名称“SME Group”是通用的，搜索结果经常与其他实体混淆，例如一家意大利电机制造商（sme-group.com）或一家美国公司；最初的机会“维护日志数据集”似乎被误解了；实际的数据机会在于其大量的采购日志、物流
- Deep Qualification80
⚠ 需要审查 — Smegroup 是一个采购和物流服务提供商，而不是指定“维护日志数据集”的直接持有者。他们拥有的数据与工业零件的供应链有关，而不是预测性维护模型所需的运营故障和维护日志。由于客户保密性，数据所有权复杂且许可受限。[许可受限；实体不持有该细分市场的特征数据：目标细分市场需要“故障报告、维护日志、传感器数据”。Smegroup 的数据是采购相关的（订单、供应商、物流），这与定义该细分市场的运营和传感器数据不同。[3, 19]；数据集类型与实际活动不符：该公司的核心业务是采购、物流和组装服务，而不是运营维护。[3, 19] 他们处理零件订购和供应链方面的数据，但不太可能拥有详细的时间序列维护日志或设备故障数据，这些数据是在客户的运营现场生成的。]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Procurement / tenders
这些文本数据详细描述了工业采购流程，为正在记录维护的设备的供应链和采购提供了有价值的背景信息。
Maintenance logs
这些核心时间序列数据记录了制造和组装过程中的服务，为训练预测性维护算法以预测设备故障提供了必需的原材料。
Industrial data
这些时间序列证据证实了数据集的广度，涵盖了从能源到医疗技术等多个工业领域的领先公司，这极大地增强了任何在其上训练的 AI 模型的鲁棒性。
Marketplace
Dataset details
Detailed schema & sample available on access request.
Want this data?
Request access — we broker a secure deal room. Operator-reviewed, no automatic sharing.
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
Smegroup 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 = $6.76B in 2023, CAGR 27.4% (source: The Insight Partners) [9]. Investment score 68.6/100 (confidence 0.49). Recommended action: Acquire.
From the marketplace
Explore live data opportunities
Storelectric — 工业传感器数据集机会
View opportunity →工业Trinityenergy — 工业传感器数据集机会
View opportunity →其他Innova Renewables — 传感器遥测数据集机会
View opportunity →