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README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+- time-series-forecasting
+- tabular-classification
+language:
+- en
+tags:
+- synthetic-data
+- web-analytics
+- event-stream
+- clickstream
+- time-series
+size_categories:
+- 10M<n<100M
+---
+
+# FreeSyntheticWebEvents50M
+
+A free dataset of 50 million fully synthetic web analytics events, built for developers and researchers who need realistic clickstream and event-stream data at scale — for testing analytics pipelines, funnel and conversion analysis, session-based recommendation, anomaly detection, or time-series and streaming tooling. No real people, sessions, or sites are represented in this data.
+
+## Schema
+
+| Column | Type | Description |
+|---|---|---|
+| event_id | string | Unique event identifier |
+| session_id | string | Synthetic session identifier |
+| user_id | string | Synthetic user identifier |
+| event_type | string | Event type (page_view, click, add_to_cart, purchase, etc.) |
+| page_url | string | Page path the event occurred on |
+| device_type | string | mobile, desktop, or tablet |
+| event_timestamp | string | Event time (YYYY-MM-DD HH:MM:SS) |
+| session_duration_sec | int | Session duration in seconds, skewed |
+
+## Format
+
+Single Parquet file, Snappy compression, ~1.6 GB, 50,000,000 rows.
+
+## Quick Start
+
+**pandas**
+```python
+import pandas as pd
+df = pd.read_parquet("events_50M.parquet")
+```
+
+**datasets**
+```python
+from datasets import load_dataset
+ds = load_dataset("ziadatalabs/FreeSyntheticWebEvents50M")
+```
+
+**duckdb**
+```python
+import duckdb
+duckdb.sql("SELECT * FROM 'events_50M.parquet' LIMIT 10").show()
+```
+
+## Notes
+
+Event timestamps follow realistic temporal patterns — busier during daytime and weekdays, sparse overnight — rather than uniform-random times, so the data is usable for time-series and anomaly-detection work. Event types follow a realistic funnel (frequent page views and clicks, rare purchases), and device split reflects typical web traffic. All entirely synthetic.
+
+## License & Usage
+
+Released under CC BY-NC 4.0 — personal, research, and educational use permitted, attribution required, no commercial use.
+
+---
+
+Created by Zia Data Labs. Questions or feedback: zia.data.team@protonmail.com