Cold Chain Logistics Temperature Logs

This dataset provides granular, time-stamped temperature and humidity logs across cold chain logistics, including shipment, container, and sensor identifiers, geolocation, and alarm events. It enables comprehensive monitoring, compliance verification, and rapid response to deviations, supporting safety and quality control for temperature-sensitive products.

  • opened 17 times
  • last updated 21 Jul 2025
  • by GoMask
The brief that made it

Real-time monitoring and alerting for temperature-sensitive shipments

Sample rows

preview · 8 of 200 rows · all 14 columns
log_idstringalarm_typestringtemperature_celsiusfloatalarm_triggeredbooleanshipment_idstringcontainer_idstringsensor_idstringtimestampdatetimehumidity_percentfloatlocation_latitudefloatlocation_longitudefloatlocation_descriptionstringoperator_idstringremarksstring
LOG00001none4.3falseSHIP1001CONT2001SENS30012024-06-01T08:15:00Z67.540.7128-74.006NYC Main WarehouseOPR001blank
LOG00002none5.1falseSHIP1001CONT2001SENS30012024-06-01T09:45:00Z65.240.7128-74.006NYC Main WarehouseOPR001blank
LOG00003none3.7falseSHIP1001CONT2001SENS30022024-06-01T12:20:00Z64.140.7128-74.006NYC Main WarehouseOPR002Routine check
LOG00004temperature_low-21.7trueSHIP1002CONT2002SENS30032024-06-02T07:50:00Z89.948.85662.3522Paris Frozen StorageOPR003Temperature dropped below threshold
LOG00005none-17.8falseSHIP1002CONT2002SENS30042024-06-02T09:10:00Z85.148.85662.3522Paris Frozen StorageOPR003Frozen shipment
LOG00006temperature_low-23.2trueSHIP1002CONT2002SENS30042024-06-02T11:00:00Z92.848.85662.3522Paris Frozen StorageOPR004Alert: Temperature out of range
LOG00007none27.6falseSHIP1003CONT2003SENS30052024-06-03T06:30:00Z63.935.6895139.6917Tokyo Distribution CenterOPR005blank
LOG00008none25.9falseSHIP1003CONT2003SENS30052024-06-03T07:00:00Z70.835.6895139.6917Tokyo Distribution CenterOPR006blank

What the 200 rows show

from the 200-row sample

Temperature_low (alarm type) stands out: mean temperature_celsius is -50.0, against 18.1 for the rest.

  • 34%alarm_triggered = true
  • 6.1median temperature_celsius
  • 70.0median humidity_percent
temperature_celsius200 rows, in bands of 20
0651309009151251314015-1000100temperature_celsius →

Median 6.1, from -100.0 to 100.0.

14 columns by typefrom the column list below
  • string 8
  • float 4
  • datetime 1
  • boolean 1

Columns

14 columns in four groups
blueprint · 14 columns
columntypedescriptionexample
Text 8 columns
log_idstringUnique identifier for each temperature and humidity log entryuniqueLOG00001
shipment_idstringUnique identifier for the shipment associated with this log entrySHIP1001
container_idstringUnique identifier for the container or storage unit being monitoredCONT2001
sensor_idstringUnique identifier for the sensor device recording the dataSENS3001
location_descriptionstringTextual description of the sensor's location (e.g., warehouse, truck, facility name)optionalNYC Main Warehouse
alarm_typestringType of alarm triggered, if any (e.g., temperature_high, temperature_low, humidity_high, humidity_low)5 values · optionalnone
operator_idstringIdentifier of the operator responsible at the time of recording (if applicable)optionalOPR001
remarksstringAdditional notes or comments about the log entryoptionalRoutine check
Numbers 4 columns
temperature_celsiusfloatMeasured temperature in degrees Celsius-100 to 1004.3
humidity_percentfloatMeasured relative humidity as a percentage (0-100%)0 to 10067.5
location_latitudefloatLatitude coordinate of the sensor at the time of recording-90 to 90 · optional40.7128
location_longitudefloatLongitude coordinate of the sensor at the time of recording-180 to 180 · optional-74.006
Dates and times 1 column
timestampdatetimeDate and time when the temperature and humidity were recorded (in UTC)2024-06-01T08:15:00Z
True or false 1 column
alarm_triggeredbooleanIndicates whether an alarm was triggered due to temperature or humidity out of rangeoptionalfalse

15 SQL practice questions for the Cold Chain Logistics Temperature Logs

Written for this data and checked against it: 12 SQL and 3 Power BI exercises from beginner to advanced. Try the first three free; the practice kit has all 15, a starter .sql file and an answer key with every expected result.

  1. 01BeginnerFreeSELECT · WHERE · ORDER BY

    High temperature alarms

    Return log_id, shipment_id and temperature_celsius for every log whose alarm_type is 'temperature_high'. Order the results by temperature_celsius from highest to lowest, then by log_id ascending.

    Tables: cold_chain_logistics_temperature_logs · your result: 3 columns, 14 rows
  2. 02BeginnerFreeDISTINCT · ORDER BY

    Distinct alarm types

    Return each distinct alarm_type found in the logs as a single column named alarm_type, ordered alphabetically.

    Tables: cold_chain_logistics_temperature_logs · your result: 1 columns, 4 rows
  3. 03BeginnerFreeGROUP BY · COUNT

    Logs per alarm type

    Count the logs for each alarm_type. Return alarm_type and log_count, ordered by log_count from highest to lowest, then by alarm_type ascending.

    Tables: cold_chain_logistics_temperature_logs · your result: 2 columns, 4 rows
  1. 04Average humidity by alarm flagBeginner
  2. 05Alarmed logs by alarm typePower BI
  3. 06Shipments with repeated alarmsIntermediate
  4. 07Temperature bucketsIntermediate
  5. 08Logs per monthIntermediate
  6. 09Shipments hotter than overall averageIntermediate
  7. 10Alarm rate by locationPower BI
  8. 11Rank shipments by max temperatureAdvanced
  9. 12Temperature change from previous logAdvanced
  10. 13Running alarm totalAdvanced
  11. 14Share of alarms by typeAdvanced
  12. 15Temperature anomalies per sensorPower BI

Get the practice kit: the full dataset, all 15 exercises, a starter .sql and the answer key. One-time $3.99.

Get the practice kit · $3.99

Use it for

  • alarm triggered34%68 of 200 rows

    A logistics dashboard

    The alarm_triggered rate and temperature_celsius by alarm_type. Excel, Power BI or Tableau.

  • Why do the 24 temperature_low rows have a mean temperature_celsius of -50.0?

    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 logs with shipment_id, container_id and sensor_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 14 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows14 columns
Yours1,000 rows14 columnslocation_latitude: UK only

blueprint · cold-chain-logistics-temperature-logs

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 14 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
  • Each row is a temperature reading by segment.
  • Location, timestamp, and shipment ID included.
  • Deviation flags for compliance breaches.
  • Product type and transporter details attached.
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
cold-chain-logistics-temperature-logs

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