Telecommunications
15 columns
150 rows
8 formats

Network Outage Events and Root Cause Analysis

This dataset provides detailed records of major network outage events, including timing, affected services, geographic impact, customer impact, root cause analysis, and post-incident reviews. It enables comprehensive incident tracking, root cause identification, and operational improvement for telecommunications networks. Ideal for reliability analytics, regulatory reporting, and service quality enhancement.

last updated 1 Nov 2025
by GoMask

The brief that made it

Network reliability and performance analytics

Sample rows

preview · 8 of 150 rows · all 15 columns

outage_idstring	incident_severitystring	customer_count_affectedinteger	affected_voiceboolean	root_causestring	outage_start_timedatetime	outage_end_timedatetime	affected_databoolean	affected_smsboolean	geo_regionstring	countrystring	post_incident_review_completedboolean	post_incident_review_datedate	root_cause_detailsstring	post_incident_actionsstring
OUT-00001	critical	102300	true	fiber cut	2021-01-01T00:05:44Z	2021-01-01T04:32:17Z	true	true	London	United Kingdom	true	2021-01-03	Major fiber cut caused by construction work near the city center; backup fiber also disrupted.	Implemented additional fiber route redundancy and improved construction monitoring protocols.
OUT-00002	minor	56	false	software bug	2021-02-14T12:14:07Z	2021-02-14T12:30:09Z	true	false	Osaka	Japan	false	blank	Unexpected error in network management software following patch deployment.	blank
OUT-00003	moderate	850	true	equipment failure	2021-03-03T23:48:05Z	2021-03-04T00:17:37Z	false	true	Berlin	Germany	true	2021-03-05	Voice gateway module malfunctioned due to aging hardware; SMS relay briefly disrupted.	Replaced gateway hardware and enhanced maintenance schedule for legacy equipment.
OUT-00004	moderate	111	false	other	2021-04-18T16:02:44Z	2021-04-18T20:04:05Z	false	true	Warsaw	Poland	false	blank	SMS center overloaded due to external spam campaign targeting local numbers.	blank
OUT-00005	major	90000	true	fiber cut	2021-05-01T08:14:30Z	2021-05-01T20:51:10Z	true	false	New York	United States	true	2021-05-03	Fiber link damaged by subway maintenance crew; primary voice/data backbone affected.	Coordinated with city utilities to establish new fiber protection policies.
OUT-00006	major	17400	false	equipment failure	2021-06-11T05:21:55Z	2021-06-11T07:06:11Z	true	true	Delhi	India	true	2021-06-12	Central data switch outage due to overheating and lack of ventilation.	Installed improved HVAC and monitoring sensors in data center.
OUT-00007	moderate	440	true	power loss	2021-07-04T23:59:56Z	2021-07-05T03:41:35Z	false	false	Cape Town	South Africa	true	2021-07-06	Unexpected power outage in the local exchange due to transformer explosion.	Installed backup generator and improved surge protection.
OUT-00008	minor	8	false	software bug	2021-08-22T17:30:10Z	2021-08-22T17:40:44Z	false	true	Reykjavik	Iceland	false	blank	SMS routing software failed during midnight system update.	blank
OUT-00009	minor	0	false	other	2021-09-09T01:07:02Z	2021-09-09T01:10:19Z	true	true	Rio de Janeiro	Brazil	false	blank	Scheduled test failure inadvertently blocked data and SMS for short period.	blank
OUT-00010	major	16900	true	equipment failure	2021-10-31T20:45:22Z	2021-11-01T00:01:33Z	true	false	Sydney	Australia	true	2021-11-02	Main voice/data gateway failed due to firmware corruption.	Upgraded firmware and implemented automated rollback protocols.
OUT-00011	minor	7	false	software bug	2022-01-01T00:00:02Z	2022-01-01T00:00:13Z	false	true	Paris	France	false	blank	Year rollover triggered a rare SMS timestamp bug.	blank
OUT-00012	major	67000	true	fiber cut	2022-02-28T14:22:40Z	2022-02-28T15:09:51Z	true	true	Chicago	United States	true	2022-03-02	Fiber backbone cut near airport due to roadwork accident.	Installed additional fiber monitoring and city coordination.
OUT-00013	moderate	98	true	equipment failure	2022-03-15T03:15:13Z	2022-03-15T04:18:22Z	false	false	Helsinki	Finland	true	2022-03-16	Voice switch failed due to misconfigured update; isolated to city center.	Improved update procedures and switch monitoring.
OUT-00014	minor	22	false	software bug	2022-04-03T10:16:50Z	2022-04-03T11:01:29Z	true	false	Canberra	Australia	false	blank	Routine update caused temporary data service outage for select users.	blank
OUT-00015	major	8400	true	power loss	2022-05-10T22:49:30Z	2022-05-11T01:04:13Z	true	false	Toronto	Canada	true	2022-05-12	Substation failure led to extended voice/data outage in metro area.	Installed new UPS and tested emergency power switchover.
OUT-00016	moderate	212	false	software bug	2022-06-18T15:34:21Z	2022-06-18T15:59:10Z	true	true	Stockholm	Sweden	false	blank	SMS and data sessions dropped due to configuration error in central switch.	blank
OUT-00017	moderate	760	true	equipment failure	2022-07-04T13:27:19Z	2022-07-04T15:41:02Z	false	true	Johannesburg	South Africa	true	2022-07-05	SMS relay and voice gateway lost connectivity due to hardware fault.	Replaced faulty hardware and improved equipment tracking.
OUT-00018	critical	94750	true	fiber cut	2022-08-12T18:29:58Z	2022-08-13T03:45:10Z	true	true	Los Angeles	United States	true	2022-08-15	Multiple fiber cuts due to wildfire damaged core transport routes.	Upgraded fiber protection and installed early fire detection sensors.
OUT-00019	minor	13	false	other	2022-09-22T04:40:44Z	2022-09-22T05:05:12Z	false	true	Cairo	Egypt	false	blank	SMS authentication server failed due to unexpected surge in requests.	blank
OUT-00020	moderate	980	true	equipment failure	2022-10-10T08:12:21Z	2022-10-10T08:38:42Z	false	true	Auckland	New Zealand	true	2022-10-11	Voice switch and SMS gateway failed due to simultaneous circuit breaker trips.	Installed new circuit breakers and improved switch monitoring.

What the 150 rows show

from the 150-row sample

Critical (incident severity) stands out: mean customer_count_affected is 73,740, against 6,064 for the rest.

49%affected_voice = true
640.5median customer_count_affected

Mean customer_count_affected by incident_severity150 rows

customer_count_affected150 rows, in bands of 20k

Median 640.5, from 0 to 102,300.

root_cause150 rows · 5 values

software bug39
equipment failure38
fiber cut35
other21
power loss17

15 columns by typefrom the column list below

string 7
integer 1
date 1
datetime 2
boolean 4

Columns

15 columns in four groups

blueprint · 15 columns
column	type	description	example
Text 7 columns
`outage_id`	string	Unique identifier for each network outage eventunique	OUT-00001
`geo_region`	string	Geographic region impacted by the outage (e.g., city, state, or region name)	London
`country`	string	Country where the outage occurred	United Kingdom
`root_cause`	string	Primary root cause of the outage5 values	fiber cut
`root_cause_details`	string	Detailed explanation of the root cause, including contributing factorsoptional	Major fiber cut caused by…
`post_incident_actions`	string	Summary of actions taken after the incident to prevent recurrenceoptional	Implemented additional fi…
`incident_severity`	string	Severity level of the outage incidentminor · moderate · major · critical	critical
Numbers 1 column
`customer_count_affected`	integer	Number of customers impacted by the outage0 or more	102300
Dates and times 3 columns
`outage_start_time`	datetime	Date and time when the outage began	2021-01-01T00:05:44Z
`outage_end_time`	datetime	Date and time when the outage was resolved	2021-01-01T04:32:17Z
`post_incident_review_date`	date	Date when the post-incident review was completedoptional	2021-01-03
True or false 4 columns
`affected_voice`	boolean	Indicates if voice services were affected during the outage	true
`affected_data`	boolean	Indicates if data services were affected during the outage	true
`affected_sms`	boolean	Indicates if SMS services were affected during the outage	true
`post_incident_review_completed`	boolean	Indicates whether a post-incident review has been completed	true

Use it for

A telecommunications dashboard
The affected_voice rate, customer_count_affected by incident_severity and a breakdown of root_cause. Excel, Power BI or Tableau.
Why do the 22 critical rows have a mean customer_count_affected of 73,740?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Outages150
OUT-00001102300critical
OUT-0000256minor
OUT-00003850moderate
A software demo
Believable outages with outage_start_time, outage_end_time and affected_voice to fill a screen in front of a buyer.

This dataset150 rows15 columns

Yours1,000 rows15 columnsgeo_region: UK only

blueprint · network-outage-events-and-root-cause-analysis

Behind this dataset

Same schema. As many rows as you need.

These 150 rows came out of a blueprint — 15 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Outage ID and classification (partial, complete, service-specific)
Start timestamp and end timestamp with duration (minutes)
Services affected: voice calls, data sessions, SMS, roaming
Geographic scope: nationwide, regional, city-level, site-specific
Customer impact: number of subscribers affected
Root cause: fiber cut, equipment hardware failure, software bug, power outage, configuration error, DDoS attack
Detection method: alarm correlation, customer complaints, monitoring tools
Resolution actions: failover, equipment replacement, software rollback

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: network-outage-events-and-root-cause-analysis

What should your data show?

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Sample rows

What the 150 rows show

Columns

Use it for

A telecommunications dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Telecommunications

What should your data show?