Data category

Energy & Utilities Data

SCADA and sensor time series, outage and fault records, and maintenance history from generation and grid assets.

Evaluate Your Data Request this type of data

Energy data from utilities links continuous telemetry to real events: alarms, outages, field findings and repairs. AI developers license this utility data to train models that predict faults and plan maintenance. DataNexx helps utilities and operators find out which records can be licensed, and arranges the licence. There is no fee to the data owner.

Why it matters for AI

Recorded, judged, resolved.

Utility records tie continuous telemetry to discrete events: the alarm, the outage, the crew's finding and the repair. Linked over years, they show how real equipment fails under real weather and load, which simulators only approximate.

Typical data

SCADA & sensor time series
Outage & fault records
Root causes
Maintenance & inspection history
Aggregated meter readings
Generation output & weather
Equipment failures & replacements
Drone & thermal inspection images

Representative workflow

Illustrative

01Asset telemetry
02Alarm or fault
03Outage record
04Field inspection
05Root cause
06Repair or replacement
07Service restored

Who typically holds it

Electricity, gas and water utilities
Renewable generation operators
Grid and network maintenance contractors
District heating and energy service companies

Potential AI applications

Fault and outage prediction
Predictive maintenance for grid assets
Load and generation forecasting
Defect detection in inspection images

Guide

What utility data do energy companies hold, and where does it live?

Telemetry flows from SCADA into a historian. Outages and faults are logged in an outage management system (OMS). Work orders and inspections sit in a CMMS or asset management system, and network maps in a GIS.

The most useful records join these systems. A fault is worth more when you can see the readings before it, the crew's finding and the repair that followed.

SCADA and sensor time series from plants, substations and networks
Alarm, fault and outage records with root causes
Maintenance, inspection and replacement history
Generation output alongside weather data
Drone and thermal inspection images

What can AI teams build with energy data?

Grid and plant models need to see how real equipment fails under real weather and load. Simulators only approximate this. Years of linked utility records show it directly.

Rare events, such as storm damage or a transformer failure, are the hardest cases to learn. Long histories contain them.

Fault and outage prediction
Predictive maintenance for grid and plant assets
Load and renewable generation forecasting
Defect detection in inspection images

What about customer data and grid security?

Meter data can reveal how a household lives, so it is personal data. It is aggregated or removed before licensing, and individual customers are never identified.

Network data raises a second issue: security. Exact asset locations, control settings and network diagrams can be sensitive. These are generalized or left out, and your security team reviews the scope. This is not legal advice; your counsel and regulator duties decide what is allowed.

How do you describe your utility data for a first assessment?

You do not need to send any data. Start with a short description: the asset types, the systems in use, the years of history and how the records link.

Say whether outage records connect to telemetry and work orders. Note any data that is restricted for security reasons. The assessment walks you through it, and we reply within 24 hours.

Example record (illustrative)

One fault event as a utility might assemble it from several systems. Field names and contents are illustrative.
Field	What it holds
Event ID	An internal code, replaced with a new random ID before licensing
Asset type	A general class, such as distribution transformer or feeder breaker
Region	A broad area only, never an exact location
Telemetry window	Load, voltage and temperature readings before and after the event
Weather	Wind, temperature and rain at the time
Outage record	Start, end and number of customers affected, in bands
Field finding	What the crew found, as a coded root cause and short note
Repair	The work done and any parts replaced

Frequently asked questions

What is energy data?

In this context, energy data means the operational records of utilities and energy operators: telemetry, outages, faults, maintenance and inspections. For AI, the value is in how these records link together over time.

Can a utility license data without exposing customers?

Yes. Meter and customer data is aggregated or removed before licensing. Models for faults and maintenance mostly need asset and network records, not customer details.

Is SCADA data too sensitive to license?

Not always. Raw time series can often be shared once asset names, exact locations and control details are removed. Your security team reviews the scope before anything moves.

Do we have to send samples of our data?

Not for the first step. The assessment uses descriptions only. Samples are shared later, under a confidentiality agreement, and only if a licence looks realistic.

Who pays for the assessment?

There is no fee to the data owner. Compensation comes from the licence, when an AI company licenses the data.

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.