Dataset opportunity
Zunder — 移动遥测数据集机会
Zunder 持有的中等规模移动遥测数据集，可用于预测性维护和异常检测。
Score
74.3
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
数据共享协议
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 = 2025 年为 92.1 亿美元，复合年增长率为 26.19%。
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.
- 🤝Data partnership
与 Gireve 和 Hubject 的互操作性合作伙伴关系，需要实时数据交换
source ↗
Profile
Dataset profile
Type
移动遥测数据集
Modality
时间序列
Sector
移动
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — GDPR 敏感（PII 审查）
Buyer persona
工业人工智能与维护优化供应商
Zunder 持有的移动遥测数据集结构为时间序列数据，其中包括来自其电动汽车充电网络的 event_streams、geo_data、iot_data 和 transaction_data。这种丰富的运营、交易和传感器数据的结合，为开发和训练预测性维护模型提供了全面的基础，能够预测硬件故障并优化充电站的维护计划。
全球预测性维护市场在 2025 年的估值为92.1 亿美元，预计将以26.19% 的复合年增长率增长。[10] 虽然数据集的访问受 GDPR、国家安全敏感性以及潜在投资者限制的约束，但这种真实运营数据的稀有性和深度为寻求在快速扩张的市场中构建高保真预测模型的 AI 买家提供了显著的竞争优势。⚠ 尽职调查（有价值的数据，可协商访问）：用户特定的充电历史受严格的 GDPR PII 保护；基础设施数据可能涉及国家安全或电网稳定性敏感性；来自主要投资者 Mirova (Natixis IM) 的潜在数据共享限制 · 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据证明 Zunder 拥有来自其在南欧的活跃充电网络的真实电动汽车遥测的稀有专有数据集。该数据的核心优势在于其详细的超快充电事件时间序列日志，可直接支持开发先进的预测性维护和电池退化模型。对于工业人工智能供应商而言，这是一个独特的机会，可以获取满足快速增长的全球预测性维护市场关键需求（预计到 2025 年将达到 92.1 亿美元）的训练数据。
See dimension details ↓- Dataset Specificity100
主导的 'iot_data'，行业移动，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
AI 买家需求旺盛，这得益于预测性维护市场的快速增长，预计复合年增长率为 26.19%。[10]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/受监管
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
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 License62
所有权=公司所有，许可=GDPR 敏感
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 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 Audit67
✓ 良好目标 — Zunder 是一个良好目标，因为它运营着一个大型实体电动汽车充电网络，作为副产品生成有价值的专有遥测数据，但其现有的第三方充电器管理 SaaS 平台表明已部分实施数据货币化策略，降低了其“休眠数据”的潜力。问题：该公司提供“SaaS 平台”来“管理和货币化您的电动充电点”，这表明他们已经从事软件销售业务；他们声称的目标是到 2025 年通过其平台“管理超过 40,000 个充电点”，这是他们计划拥有的数量的 10 倍，表明重点突出；该公司最初是设计充电点管理软件，然后才建立实体网络，因此数据/软件是其核心 DNA，而不仅仅是
- Deep Qualification90
✓ 通过 — Zunder 是一个数据持有者，运营自己的电动汽车充电网络，并向其他运营商销售 SaaS 平台，作为副产品生成丰富的遥测数据集。2024 年 7 月的 2.25 亿欧元融资用于支持大规模扩张，使其成为首选目标，尽管其数据是专有和客户拥有的混合体，并受 GDPR 管辖。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
该数据集包含详细的实时时间序列数据，捕获充电硬件的电气性能，包括功率输出和电压波动，这对于预测组件故障至关重要。
Event streams
它包括详细的技术事件日志，记录了不同的电动汽车型号如何响应超快充电，为训练预测电池退化的 AI 模型提供了宝贵的真实数据。
Geospatial data
该数据集提供高分辨率的电动汽车交通流量和车站利用率模式的表格数据，使买家能够模拟实际运营压力并优化维护后勤。
Transaction data
它提供汇总的交易数据，详细说明了按车辆类型的充电频率和能源消耗，为使用模式增加了关键的上下文，以实现更准确的预测建模。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Zunder Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance Market = $9.21B in 2025, CAGR 26.19% (source: Precedence Research). Investment score 74.3/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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