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README.md

@@ -6,24 +6,24 @@ task_categories:
 language:
 - en
 tags:
+- smart-factory
+- sensor-data
+- industry-4-0
 - industrial-iot
-- edge-analytics
 - predictive-maintenance
-- test-data
-- iot
-- synthetic-data
-- sensor-data
-- smart-factory
-- machine-monitoring
-- anomaly-detection
-- manufacturing
 - telemetry
+- synthetic-data
 - mindweave
-- industry-4-0
 - time-series
-pretty_name: IoT Sensor Telemetry (Synthetic)
+- iot
+- test-data
+- edge-analytics
+- anomaly-detection
+- manufacturing
+- machine-monitoring
+pretty_name: IoT Sensor Telemetry (Synthetic) (Free Sample)
 size_categories:
-- 10K<n<100K
+- 1K<n<10K
 configs:
 - config_name: anomaly_events
   data_files: data/anomaly_events.csv
@@ -34,7 +34,9 @@ configs:
   data_files: data/telemetry_readings.csv
 ---
 
-# IoT Sensor Telemetry (Synthetic)
+# IoT Sensor Telemetry (Synthetic) (Free Sample)
+
+> **This is a free sample** with 5,003 rows. The full dataset has **50,006 rows** across 3 tables.
 
 High-frequency telemetry from a simulated smart factory operating three
 CNC lines, a finishing cell, and a predictive-maintenance program over
@@ -48,23 +50,39 @@ equipment failure event. Useful for time-series analytics, anomaly
 detection, edge telemetry pipelines, and Industry 4.0 monitoring demos.
 
 
-## Tables
+## Sample tables
+
+| Table | Sample Rows |
+|-------|------------|
+| anomaly_events | 2 |
+| sensors | 1 |
+| telemetry_readings | 5,000 |
+| **Total** | **5,003** |
+
+## Full dataset
+
+The complete dataset includes all tables with full row counts:
 
-| Table | Rows |
-|-------|------|
+| Table | Full Rows |
+|-------|----------|
 | anomaly_events | 2 |
 | sensors | 4 |
 | telemetry_readings | 50,000 |
 | **Total** | **50,006** |
 
-## Formats
+**Formats included:** CSV, Parquet, SQLite
 
-- CSV (in `data/` directory)
-- Parquet (available in full version)
-- SQLite (available in full version)
+**[Get the full dataset on Gumroad](https://mindweavetech.gumroad.com)**
 
 ## About
 
-Generated by [Mindweave Technologies](https://mindweave.tech) — realistic synthetic datasets for developers, QA teams, and data engineers.
+Generated by [Mindweave Technologies](https://mindweave.tech) -- realistic synthetic datasets for developers, QA teams, and data engineers.
+
+Every dataset features:
+- Enforced foreign key relationships across all tables
+- Realistic statistical distributions (not uniform random)
+- Temporal patterns (seasonal, time-of-day, day-of-week)
+- Injected anomalies for ML training and anomaly detection
+- Deterministic generation (same seed = same output)
 
-Browse all datasets: [mindweavetech.gumroad.com](https://mindweavetech.gumroad.com)
+Browse all datasets: [https://mindweavetech.gumroad.com](https://mindweavetech.gumroad.com)

data/sensors.csv

@@ -1,5 +1,2 @@
 id,name,metric_type,unit,machine_id,line_id,install_date
 1,SEN-001,vibration,mm_s,CNC-04,machining-a,2023-09-12
-2,SEN-002,temperature,celsius,FURN-02,heat-treat,2023-10-03
-3,SEN-003,pressure,bar,HYD-07,press-line,2023-08-19
-4,SEN-004,humidity,percent,PAINT-01,finishing,2023-11-01