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annotations_creators:
- machine-generated
language:
- en
license: cc-by-4.0
tags:
- finance
- news
- gics
- ai-training
- banking
- structured-data
- jsonl
size_categories:
- 1K<n<10K
---
# BWB Global Intelligence Pack — Free Sample
> **🛒 Want the full dataset?** → [**data.bankingwithbilly.com**](https://data.bankingwithbilly.com)
> Basic: 1,000 records / **$5** · Pro: 5,000 records / **$10** · Archive: 15,000 records / **$20** · One-time, instant download.
## Overview
A combined free sample of structured, AI-ready financial news, GICS intelligence, and long-form books from the Banking With Billy autonomous publishing network.
This **free sample** contains **650 records** from the Banking With Billy autonomous publishing network — 500+ live sites publishing continuously, 24/7 across 187 countries, 11 GICS sectors, and 156 industries.
### Families Included
- **World News Intelligence** — 187-country global news, guardian-verified, GICS-tagged
- **GICS Sector Intelligence** — 11 sectors × 156 industries, structured financial analysis
- **Long-Form Book Intelligence** — 12-chapter expert books, 1,000–2,000 words per chapter
## Schema (Omega Master Schema)
```json
{
"omega_id": "string — unique record ID",
"source_family": "string — dataset family",
"gics_sector": "string — GICS sector",
"gics_industry": "string — GICS industry",
"data_type": "news | book | government | signal",
"timestamp": "ISO-8601",
"region": "string — country or region",
"entities": ["array", "of", "named", "entities"],
"metadata": {
"confidence": 0.95,
"guardian_verified": true,
"word_count": 750,
"author": "Billy Odell Tucker-Robinson",
"license": "CC BY 4.0 — Banking With Billy"
},
"payload": {
"headline": "string",
"lead": "string",
"body": "string — full article body",
"why_it_matters": "string — Billy's expert analysis"
}
}
```
## Usage
```python
import json
records = [json.loads(line) for line in open("data.jsonl") if line.strip()]
# By GICS sector
financials = [r for r in records if r["gics_sector"] == "Financials"]
# All headlines
headlines = [r["payload"]["headline"] for r in records]
# pandas
import pandas as pd
df = pd.read_json("data.jsonl", lines=True)
print(df.groupby("gics_sector").size())
```
## Stats
| Metric | Value |
|---|---|
| Articles Written | 53,995+ |
| Books Published | 12,210+ |
| Live Indexed URLs | 22.3M+ |
| Live Sites | 500+ |
| Countries Covered | 187 |
| GICS Sectors | 11 |
| Industries | 156 |
| Update Rate | ~12 articles/hour |
## License
CC BY 4.0 — Attribution: **Banking With Billy** / Billy Odell Tucker-Robinson
## Full Dataset Access
This sample contains a fraction of available data. For full access:
👉 **[data.bankingwithbilly.com](https://data.bankingwithbilly.com)** — $5 / $10 / $20 one-time payment, instant JSONL download.
## Citation
```bibtex
@dataset{bwb_data_2026,
author = {Tucker-Robinson, Billy Odell},
title = {BWB Global Intelligence Pack — Free Sample},
year = {2026},
publisher = {Banking With Billy},
url = {https://data.bankingwithbilly.com},
license = {CC BY 4.0}
}
```
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