Dataset opportunity
Easyvirt — Sensor Telemetry Dataset Opportunity
Large sensor telemetry dataset held by Easyvirt, usable for Predictive Maintenance and Anomaly Detection.
Score
77.4
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
63%
Action
Acquire
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
Global **Predictive Maintenance** market = **$14.29 billion in 2025**, projected to reach **$98.16 billion by 2033** with a **CAGR of 27.9%** from 2026 to 2033.
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-03
Territoires connectés : quand le datacenter redessine l'économie locale
maddyness.com ↗ - 📰press2026-06-02
IA : La course aux GPU est morte. Vive les mégawatts !
maddyness.com ↗ - 📰press2026-05-28
Quelles qualifications pour les acteurs de l’informatique en nuage (cloud) ?
cnil.fr ↗ - 📰press2026-04-20
7 data center trends to watch—as seen at Data Centre World London 2026
iot-analytics.com ↗
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 📦Data product
Core products (DC Scope, CO2 Scope, DC NetScope) are data-driven intelligence solutions for IT infrastructure optimization and environmental impact.
source ↗ - 🤝Data partnership
Partnerships with Vates, Metanext, Hubblo for data integration, analysis, and Green IT solutions.
source ↗ - 📝Published article
Blog posts and customer testimonials frequently highlight 'data collection,' 'analysis,' 'real-time data,' and 'measurable data' as core to their offerings.
source ↗ - ✨Signal
40% of staff are researchers and PhDs in IT, indicating strong R&D focus on data science and analytics.
source ↗
Profile
Dataset profile
Type
Sensor Telemetry Dataset
Modality
Time Series
Sector
other
Volume
Large
Freshness
Real-time
Rarity
High (proprietary)
Accessibility
Partial
Legal
Mixed ownership — clean to license
Buyer persona
Industrial AI & maintenance-optimization vendors
Easyvirt holds a Sensor Telemetry Dataset of Time Series data, comprising industrial_data and IoT data collected from client IT infrastructures. This rich data is highly valuable for Predictive Maintenance applications, enabling the identification of patterns and anomalies to foresee potential equipment failures.
The market for such data is experiencing significant growth, driven by the need to reduce costly unplanned downtime. The global Predictive Maintenance market was valued at approximately $14.29 billion in 2025 and is projected to reach $98.16 billion by 2033, with a CAGR of 27.9%. Despite the raw data being customer-owned and requiring read-only permissions, Easyvirt's proprietary layer of aggregated, anonymized data and derived insights offers substantial business value for AI buyers, mitigating access complexity and providing ready-to-use intelligence. ⚠ Diligence (valuable data, access to negotiate): Raw data is collected from client IT infrastructures and is customer-owned.; Access to client environments requires read-only permissions.; Proprietary layer consists of aggregated, anonymized data and derived insights. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
- Dataset Specificity74
dominant 'iot_data', sector other, 3 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume80
5 evidence hits, explicit data-volume mention
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
fit for Predictive Maintenance
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
The AI-driven predictive maintenance market, which relies heavily on sensor telemetry data, is valued at USD 1.77 billion in 2025 and is projected to reach USD 19.27 billion by 2032, growing at a CAGR of 39.5%.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility62
open/API access
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility4
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength86
5 evidence types, 5 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License58
ownership=mixed, licensing=clean
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation90
4 data-appetite signals (4 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high, 4 recent external signals — proprietary data beyond what's already monetised
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 Audit42
⚠ review — Easyvirt is a software vendor whose core business is selling IT optimization and environmental impact analysis software, which constitutes selling intelligence derived from data, thus making them an unsuitable target for a data marketplace seeking companies with dormant data. Issues: Easyvirt's core business is selling software that provides intelligence (analytics, optimization, reporting) based on data collected from client IT infrastructu; The data Easyvirt handles is an input to t
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
This evidence collectively proves Easyvirt possesses a proprietary, high-granularity Time Series dataset derived from real-time monitoring of diverse industrial IT infrastructure. This data is critical for Industrial AI and maintenance-optimization vendors seeking to capitalize on the rapidly expanding Predictive Maintenance market. It directly fuels advanced predictive analytics models, enabling proactive identification of equipment failures and optimization of operational efficiency. With the market projected to grow from $14.29 billion in 2025 to $98.16 billion by 2033, access to such proprietary sensor telemetry is highly valuable for gaining a competitive edge now.
API access
This evidence confirms Easyvirt's capability to integrate with a wide array of IT monitoring protocols (e.g., API, IPMI, SNMP, CLI/SSH), ensuring comprehensive data capture from diverse industrial systems.
IoT / sensor data
This highlights the collection of real-time, fine-grained IoT data from infrastructure, providing the essential sensor telemetry for detailed operational insights and predictive modeling.
Industrial data
This specifically details the measurement and analysis of data center activity and virtualized servers, offering a critical view into the health and resource utilization of core industrial IT assets.
Event streams
This demonstrates the robust collection of real-time VM metrics and infrastructure indicators, crucial for trend analysis, capacity planning, and early detection of anomalies in complex environments.
Data-volume signal
This confirms Easyvirt's proven ability to store and analyze millions of data points, underscoring the scalability and depth of the dataset, which is vital for training sophisticated predictive AI models.
Coverage
Scanned sources
Deliverable
Premium dataset report
Easyvirt Sensor Telemetry — a Large sensor telemetry dataset (Time Series modality) in the other domain. Primary AI use-case: Predictive Maintenance. Market signal: Global **Predictive Maintenance** market = **$14.29 billion in 2025**, projected to reach **$98.16 billion by 2033** with a **CAGR of 27.9%** from 2026 to 2033.. Investment score 77.4/100 (confidence 0.63). Recommended action: Acquire.