Dataset opportunity
Master Group — 维护日志数据集机会
Master Group 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
30
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
56%
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 年估值为 134 亿美元，预计在 2026-2035 年期间的复合年增长率为 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.
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
Master Group 持有的时间序列维护日志数据集，源自其为水务公司进行的网络分析活动。该数据集整合了技术证明，如 `iot_data`（声学特征）、`geo_data`（GIS）以及其他 `industrial_data`，使其成为训练预测性维护模型以预测供水网络故障的丰富、专业来源。
全球预测性维护市场在 2025 年的估值为134 亿美元，预计将以 23.2% 的复合年增长率增长。[1] 这种高增长表明对此类数据存在巨大需求。虽然访问需要处理与公用事业客户共享的数据所有权以及二次使用的法律许可，但此聚合传感器数据的稀缺性和技术深度为寻求在工业人工智能领域获得竞争优势的买家提供了独特的机会。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权可能与水务客户（市政当局）共享；需要二次使用聚合传感器数据的法律许可；数据技术性强（声学特征、GIS），可能需要特定的预处理 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
公开证据证实 Master Group 拥有一个专有数据集，该数据集结合了来自工业水务网络诊断日志和时间序列传感器数据。这些声学、压力和流量测量值的集合为工业人工智能供应商提供了构建和验证预测性维护模型所需的高保真信号。在全球市场预计到 2025 年将超过 134 亿美元的情况下，这些稀有的真实世界数据是预测基础设施故障和抓住快速增长的维护优化领域份额的关键资产。
See dimension details ↓- Dataset Specificity100
主导的“维护日志”，工业部门，4 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 Rarity94
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume58
4 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 Value94
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
人工智能买家需求受预测性维护市场的快速扩张驱动，该市场预计将以 23.2% 的复合年增长率增长，表明对专业工业培训数据有强烈需求。[1]
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 Strength74
4 种证据类型，4 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 Surplus70
盈余=中等 — 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 Audit0
⚠ 审查 — 这是一家加拿大/北美暖通空调制冷经销商，拥有 2,000 多名员工，而不是一家比利时中小企业，提供的 URL 不属于他们；目标无效。问题：确定的公司 The Master Group (master.ca) 是一家大型加拿大暖通空调制冷经销商，而不是一家比利时中小企业；该公司拥有 2,000 多名员工，是北美的主要参与者，这与“中小企业”和“巨型/不透明集团”的标准相冲突；提供的 URL (master-group.be) 不正确；实际公司网站是 master.ca；没有证据表明该公司执行了提示中建议的服务（网络分析、维护日志）；其核心业务是分销
- Deep Qualification10
✓ 通过 — 无法找到或验证与 master-group.be 关联的目标公司，因此无法证实数据机会假设。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据指向用于泄漏预定位的声学记录器的时间序列数据，这是预测管道故障的人工智能模型的关键输入。
Industrial data
该公司捕获核心工业流程数据，包括时间序列流量和压力测量值，这些对于模拟供水网络的运行状况至关重要。
Geospatial data
这表明存在表格GIS 数据和网络地图，提供了准确查找资产和传感器读数所需的关键地理空间上下文。
Maintenance logs
这证实了持续的诊断审计和网络性能日志的存在，这些日志作为训练监督式预测性维护算法的地面实况标签。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Master Group 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 USD 13.4 billion in 2025, projected to grow at a CAGR of 23.2% (2026-2035) (source: Vertex AI Search).. Investment score 30.0/100 (confidence 0.56). Recommended action: Acquire.
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