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DataNexx

Data category

Telecom & Network Data

Network performance and fault logs, outage tickets with root causes, and field technician records.

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Telecom data for AI is the operational record of a network: performance logs, alarms, fault tickets, root causes and field fixes. AI teams use it to predict faults, find root causes and plan capacity. Linked together, these records show how problems spread and get fixed across a large network. DataNexx helps operators and network contractors license them with subscriber data excluded or aggregated.

Why it matters for AI

Recorded, judged, resolved.

Telecom operators log every alarm, ticket and fix. Linked together, these records show how faults propagate and get resolved across large networks — operational knowledge that rarely leaves the network operations center. Subscriber data is excluded or aggregated.

Typical data

  • Network performance logs
  • Fault & alarm logs
  • Outage tickets & root causes
  • Field technician jobs
  • Aggregated traffic & capacity
  • Support conversations & resolutions
  • Anonymized churn records

Representative workflow

Illustrative

  1. 01Network alarm
  2. 02Fault ticket
  3. 03Remote diagnosis
  4. 04Field dispatch
  5. 05Root cause
  6. 06Fix
  7. 07Service restored

Who typically holds it

  • Mobile and fixed-line operators
  • Internet service providers
  • Network maintenance contractors
  • Tower and infrastructure companies

Potential AI applications

  • Network fault prediction
  • Root-cause analysis agents
  • Capacity planning
  • Customer-support assistants

Which systems hold telecom network data?

Network management systems hold performance counters and alarms. The trouble-ticket system holds faults, diagnoses and fixes. Field-service tools hold technician jobs, parts and photos. Inventory systems hold sites, equipment and links.

The chain from alarm to fix is the core asset. It shows which alarms mattered and what actually solved the problem. Years of these chains also show seasonal patterns, such as storm damage or holiday traffic peaks.

  • Alarm and fault logs with timestamps
  • Outage tickets with recorded root causes
  • Field technician jobs with the fix applied
  • Aggregated traffic and capacity trends

What do AI teams build with telecom data?

Teams train fault prediction on alarms that came before real outages. They build root-cause agents that walk through a ticket the way an engineer would. They plan capacity from years of aggregated traffic.

Support assistants learn from tickets too. A resolved case shows which questions led to the fix.

Tower and infrastructure companies hold a related record. Site visits, power issues and equipment swaps over many years show how physical assets fail.

Which privacy rules apply to telecom data?

Subscriber data is tightly protected. In the US, rules on customer proprietary network information (CPNI) limit how carriers use and share call and usage records. Similar rules apply in many other countries.

So subscriber records, call details and locations are excluded or aggregated. Network data from equipment, alarms and tickets is the main focus. Security-sensitive details, such as site access or configurations, are removed too. Lawful-intercept and law-enforcement request records are never included.

How does an operator prepare a first description?

A short description is enough to start. No network data is shared.

  • Network types: mobile, fixed, fibre or transport
  • Number of years of alarms and tickets, roughly
  • Whether root causes are recorded on closed tickets
  • Which data your security team will not release

Example record (illustrative)

Illustrative record: a fictional, de-identified outage ticket. Not a real network.
FieldWhat it holds
Alarm sequencePower alarm, then link-down alarms on three cells
Ticket priorityHigh, customer-affecting
Remote diagnosisBattery backup failing after a mains outage
Field actionTechnician replaced the battery string on site
Root causeAged batteries past their replacement date
RedactionsSite IDs, locations and staff names replaced with tokens

Frequently asked questions

Is subscriber data included?

No. Subscriber records, call details and locations are excluded or aggregated. The focus is network operations data.

What telecom data is most useful for AI?

Alarms linked to tickets, root causes and the fix. That chain teaches models how faults spread and get resolved.

Can network contractors take part?

Yes, for records they hold the rights to. Often the operator's authorization is also needed.

What about security-sensitive details?

Site access details, configurations and anything your security team flags are removed before licensing.

Is there a fee for the operator?

No. There is no fee to the data owner. Compensation comes from the licence with the AI company.

How quickly do you reply?

We reply within 24 hours. The first step is a short description of your network records.

Sources

Trust & compliance

Data licensing without losing control.

Your data stays yours until you decide otherwise. We assess before anything is shared, and we treat rights and privacy as conditions of a transaction — not afterthoughts.

No raw data for an initial evaluation

Nothing moves without authorization

Ownership is not the same as licensing rights

Specialist review where it is needed

Scoped records, never bulk exports

How we handle rights, privacy and confidentiality

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