Network Performance Degradation and Quality Issues

This dataset provides granular records of network performance degradation events, capturing details such as event type, severity, affected KPIs, user impact, and resolution status. It enables telecom operators to analyze quality issues, correlate degradations with network metrics, and improve service reliability through actionable insights.

  • opened 8 times
  • last updated 1 Nov 2025
  • by GoMask
The brief that made it

Root cause analysis of network quality issues

Sample rows

preview · 8 of 700 rows · all 20 columns
event_idstringnetwork_segment_typestringaffected_users_countintegerreported_by_userbooleanevent_typestringevent_start_timedatetimeevent_end_timedatetimenetwork_segment_idstringseverity_levelstringuser_report_idstringkpi_affectedstringkpi_value_beforefloatkpi_value_duringfloatkpi_thresholdfloatlocation_latitudefloatlocation_longitudefloatroot_causestringresolution_statusstringresolution_timedatetimeadditional_notesstring
EVT-0001backbone10043falsecongestion2024-06-03T08:14:32Z2024-06-03T11:56:32ZBKB-112criticalblankthroughput87.26.11537.7749-122.4194Upstream ISP overloadresolved2024-06-03T12:08:19ZTraffic rerouted, normal operation restored.
EVT-0002cell0falsepacket_loss2024-06-02T20:05:09Z2024-06-02T22:10:15ZCELL-4082majorblankpacket_loss_rate0.010.670.1540.7128-74.006Severe weather interferenceresolved2024-06-02T22:25:10ZCell returned to service after storm passed.
EVT-0003site1trueuser_reported_issue2024-06-04T09:23:44ZblankSITE-2038minorUSR-45823latency34.5143.86051.5074-0.1278User device misconfigurationinvestigatingblankUser contacted support, analysis ongoing.
EVT-0004region8943trueslow_data_speed2024-06-05T13:11:56ZblankREGION-502criticalUSR-45824throughput70.12.41035.6895139.6917Fiber cut due to construction accidentopenblankField team dispatched for emergency repair.
EVT-0005region27falseintermittent_connectivity2024-06-03T03:17:09Z2024-06-03T05:49:15ZREGION-914minorblankavailability99.9287.395-33.8688151.2093Temporary traffic reroutingresolved2024-06-03T06:02:31ZConnectivity stabilized after routing update.
EVT-0006site188falsehigh_latency2024-06-02T15:41:21Z2024-06-02T17:09:12ZSITE-6012majorblanklatency44.7211.812048.85662.3522Software update caused delaysresolved2024-06-02T17:29:33ZRollback applied, latency returned to baseline.
EVT-0007siteblankfalsethreshold_violation2024-06-04T19:26:05Z2024-06-04T22:10:31ZSITE-6078minorblanklatency29.887.66052.5213.405Temporary backhaul congestionresolved2024-06-04T22:25:14ZThresholds re-applied, event closed.
EVT-0008cell87trueintermittent_connectivity2024-06-01T21:00:12ZblankCELL-1034majorUSR-45825availability99.892.195-90180Unstable cell tower firmwareinvestigatingblankFirmware patch scheduled for next maintenance window.

What the 700 rows show

from the 700-row sample

Backbone (network segment type) stands out: mean affected_users_count is 12,152, against 1,673 for the rest.

  • 35%reported_by_user = true
  • 29.5median affected_users_count
  • 3severity levels
  • 4resolution statuses
  • 5kpi affecteds
  • 39.8median kpi_value_before
Mean affected_users_count by network_segment_type698 rows
010k20k90.0cell214 rows3,779site228 rows860.1region174 rows12,152backbone82 rows
affected_users_count698 rows, in bands of 2,000
026052051711193473431008,00016kaffected_users_count →

Median 29.5, from 0 to 14,480.

event_type700 rows · 7 values
  1. packet_loss126
  2. slow_data_speed119
  3. threshold_violation111
  4. intermittent_connectivity108
  5. user_reported_issue106
  6. congestion74
  7. high_latency56
20 columns by typefrom the column list below
  • string 10
  • integer 1
  • float 5
  • datetime 3
  • boolean 1

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 10 columns
event_idstringUnique identifier for each network performance degradation eventuniqueEVT-0001
event_typestringType of degradation event (e.g., slow_data_speed, high_latency, packet_loss, intermittent_connectivity, congestion, threshold_violation, user_reported_issue)7 valuescongestion
network_segment_idstringIdentifier for the affected network segment (cell, site, region, etc.)BKB-112
network_segment_typestringType of network segment (e.g., cell, site, region, backbone)cell · site · region · backbonebackbone
severity_levelstringSeverity of the event (e.g., minor, major, critical)minor · major · criticalcritical
user_report_idstringReference to the user report if availableoptionalUSR-45823
kpi_affectedstringKey network performance indicator affected (e.g., throughput, latency, packet_loss_rate, jitter, availability)5 valuesthroughput
root_causestringIdentified root cause of the event if availableoptionalUpstream ISP overload
resolution_statusstringCurrent status of the event resolution (e.g., open, investigating, resolved, closed)open · investigating · resolved · closedresolved
additional_notesstringAdditional notes or comments about the eventoptionalDevice sweep scheduled.
Numbers 6 columns
affected_users_countintegerNumber of users affected by the event0 or more · optional10043
kpi_value_beforefloatValue of the affected KPI before the eventoptional87.2
kpi_value_duringfloatValue of the affected KPI during the event6.1
kpi_thresholdfloatThreshold value for the KPI that was violatedoptional15
location_latitudefloatLatitude of the affected network segment-90 to 90 · optional37.7749
location_longitudefloatLongitude of the affected network segment-180 to 180 · optional-122.4194
Dates and times 3 columns
event_start_timedatetimeTimestamp when the degradation event started2024-06-03T08:14:32Z
event_end_timedatetimeTimestamp when the degradation event endedoptional2024-06-03T11:56:32Z
resolution_timedatetimeTimestamp when the event was resolvedoptional2024-06-03T12:08:19Z
True or false 1 column
reported_by_userbooleanIndicates if the event was reported by a userfalse

Use it for

  • reported by us…35%246 of 700 rowsmean affected users c…90.0cell3.8ksite860.1regi…12.2kback…

    A telecommunications dashboard

    The reported_by_user rate, affected_users_count by network_segment_type and a breakdown of event_type. Excel, Power BI or Tableau.

  • Why do the 82 backbone rows have a mean affected_users_count of 12,152?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable events with event_type, event_start_time and event_end_time to fill a screen in front of a buyer.

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This dataset700 rows20 columns
Yours1,000 rows20 columnslocation_latitude: UK only

blueprint · network-performance-degradation-and-quality-issues

Behind this dataset

Same schema. As many rows as you need.

These 700 rows came out of a blueprint — 20 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
  • Degradation event ID and detection timestamp
  • Issue type: slow data throughput, high latency, packet loss, intermittent disconnects
  • Affected area: cell ID, region, service type
  • KPI thresholds violated: e.g., latency >100ms, packet loss >1%, throughput <1Mbps
  • Duration: minutes or hours of degraded performance
  • User-reported issues: complaint correlation from customer care
  • Root cause: network congestion, backhaul capacity, RF interference, configuration
  • Impact severity: minor (few users), moderate, significant (widespread complaints)
Rows
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Exports
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Licence
yours to use, including commercially
API slug
network-performance-degradation-and-quality-issues

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