Dataset opportunity
Gotoglobal — 出行遥测数据集机会
Gotoglobal 持有的中等规模出行遥测数据集，可用于预测性维护和异常检测。
Score
48
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
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)
全球预测性车队维护市场规模在 2024 年达到 52 亿美元，预计到 2033 年将达到 251 亿美元，复合年增长率为 18.1%（来源：Dataintelo）。[11]
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
出行遥测数据集
Modality
时间序列
Sector
出行
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
混合所有权 — GDPR 敏感（PII 审查）
Buyer persona
工业人工智能与维护优化供应商
Gotoglobal 拥有丰富的出行遥测数据集，结构为时间序列数据，整合了 `geo_data`、来自车辆传感器的 `iot_data` 和 `transaction_data`。这些精细的真实世界数据非常适合训练预测性维护模型，以预测车辆组件故障并优化维护计划，因为它提供了车队运营的全面视图。
该价值体现在全球预测性车队维护市场，该市场在 2024 年达到 52 亿美元，并预计以 18.1% 的复合年增长率增长，到 2033 年将达到 251 亿美元。[11] 虽然访问需要处理GDPR/隐私敏感性以及混合数据所有权模型，但该集成数据集的稀有性和深度使其成为寻求在此高增长市场中获得竞争优势的买家的宝贵资产。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据包括高分辨率 GPS 和用户 PII，使其对 GDPR/隐私敏感；混合业务模式：拥有/运营车队（自有数据）同时提供 SaaS 平台（客户自有数据）；上市公司地位（TASE: GOTO）意味着结构化的合规和治理要求 · 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 Gotoglobal 拥有来自大型、积极管理、跨国车队的实时遥测的专有、高稀有性数据集。这正是工业人工智能供应商寻求开发和训练复杂的预测性维护算法所需的地面实况数据。在全球预测性车队维护市场预计到 2033 年将达到 251 亿美元的情况下，该数据集通过实现更准确的故障预测和维护优化模型，提供了显著的竞争优势。
See dimension details ↓- Dataset Specificity90
主导的 'iot_data'，出行行业，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 Demand90
人工智能买家需求旺盛，这得益于预测性车队维护市场的显著增长，该市场正以 18.1% 的复合年增长率扩张。[11]
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 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 License28
所有权=混合，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 Orientation73
3 个数据需求信号（3 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，2 个近期外部信号 — 超出已货币化的专有数据
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 Audit75
⚠ 审查 — GoTo Global 运营着一个真实的共享出行车队，生成有价值的遥测数据，但也明确地将其技术作为白标 SaaS 平台提供给其他车队运营商，使其成为技术供应商，因此不适合。问题：公司网站和投资者关系材料明确表示，他们将其出行平台作为白标技术解决方案提供给其他企业；这种销售技术平台/SaaS 的业务模式与‘不良目标’定义直接冲突，因为他们正在销售智能/软件；与 GoTo（前 LogMeIn）这家非常大的美国 SaaS 公司存在高度混淆的风险。目标公司是以色列的 GoTo Global。
- Deep Qualification90
✓ 通过 — 目标是数据持有者，而非销售者；其核心业务是共享出行服务和提供车队管理平台。‘出行遥测数据集’是其运营的连贯副产品。数据所有权是混合的，涉及其自有车队的公司数据及其 SaaS 客户的客户数据，使其在 GDPR 下高度敏感。2026 年 6 月的一份近期财务报告提供了及时的触发。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>WeaveGrid, a grid-edge orchestration software provider for electric utilities, is collaborating with GM Energy to support access to utility programs across the country. The collaboration is aligned with General Motors’ vehicle-to-grid (V2G) efforts and is designed to help eligible Chevrolet, GMC, and Cadillac EV drivers participate in utility programs that can help support a more […]</p> <p>The post <a href="https://www.powermag.com/weavegrid-gm-advance-grid-integrated-ev-charging-and-home-energy-programs/">WeaveGrid, GM Advance Grid-Integrated EV Charging and Home Energy Programs</a>”
- “La maison mère de MG Motor change de directeur général en France. Vincent Zuo, qui a déjà travaillé en Italie et dans les pays nordiques pour SAIC, succède à Haojie Guo qui rejoint le siège du constructeur en Chine.”
IoT / sensor data
这是来自车辆物联网传感器的时间序列数据，对于构建预测性维护模型以分析车辆健康状况和预测组件故障的人工智能供应商至关重要。
Geospatial data
这些表格数据证实了车队在多个国家/地区的地理多样性和规模，这对于训练能够跨不同运营环境和气候泛化的稳健模型至关重要。
Transaction data
这些表格数据通过庞大的客户群展示了高车队利用率，提供了丰富的使用模式，这对于模拟车辆组件的实际应力和磨损至关重要。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Gotoglobal Mobility Telemetry — a Moderate mobility telemetry dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Fleet Maintenance market size reached $5.2 billion in 2024, projected to reach $25.1 billion by 2033, CAGR 18.1% (source: Dataintelo). [11]. Investment score 48.0/100 (confidence 0.49). Recommended action: Data Sharing Agreement.
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