IoT Sensor Data Analysis: Resampling, Thresholds, Drift & Uptime
Find gaps in timestamps, resample to hourly averages, measure threshold excursions, compute uptime and completeness, track calibration drift with SLOPE, smooth noise, build hysteresis alarms and a compliance report with MKT: 8 graded labs on a fictional cold-storage warehouse.
The first lesson is free — no account needed.
About this course
An IoT sensor data analysis course that works through the temperature data of one fictional cold-storage warehouse in a spreadsheet, for IoT and data engineers, quality and cold-chain staff and data analysis students. You turn timestamps into sampling intervals and find the gaps and the longest outage, resample 15-minute readings to hourly means and maxima with HOUR and AVERAGEIFS, flag readings outside 2–8 °C and measure the minutes out of range and the longest excursion, compare data completeness with gateway uptime for four sensors, track calibration drift against a reference probe with SLOPE and predict with FORECAST when a sensor leaves its tolerance, smooth noise with a moving average, compare a simple threshold alarm with a hysteresis alarm by the notifications sent and build a two-week compliance report with time in range and the mean kinetic temperature. The first lab is free.
Lessons
- Timestamps & Sampling Intervals: Finding the GapsFree
- Resampling to Hourly Averages with HOUR & AVERAGEIFS Pro
- Threshold Excursions: Count, Minutes & the Longest Excursion Pro
- Sensor Uptime & Data Completeness % Pro
- Calibration Drift vs a Reference Sensor: SLOPE & FORECAST Pro
- Smoothing: Moving Average vs Raw Noise (with a Chart) Pro
- Alert Rules with Hysteresis: ON above X, OFF below Y Pro
- Compliance Report: Daily Status, Time in Range, MKT & a Chart Pro