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README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+  - text-classification
+  - feature-extraction
+  - tabular-classification
+language:
+  - en
+  - multilingual
+tags:
+  - companies
+  - business
+  - lead-generation
+  - b2b
+  - firmographic
+  - company-data
+  - credit-scoring
+  - financial-data
+  - global-companies
+pretty_name: "World Company Database — Premium 1M (Revenue + Credit Score)"
+size_categories:
+  - 100K<n<1M
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: premium-1m-companies.parquet
+---
+
+# World Company Database — Premium 1M Sample
+
+**1,000,000 curated companies** with verified revenue data and credit scores, extracted from the [S.C.A.L.A. Score](https://score.get-scala.com) global company database containing **272+ million records**.
+
+## What Makes This Premium
+
+Unlike random company samples, **every record in this dataset** has:
+
+- **Actual revenue data** (revenue > 0) — no empty financial fields
+- **Credit score >= 50** — only creditworthy, financially assessed companies
+- **Sorted by revenue** — the largest companies in each country come first
+
+This is the top slice of 2.3 million financially enriched records out of 272M+ total.
+
+## Dataset Description
+
+This dataset provides high-quality structured firmographic and financial data for 1 million companies across 13 European countries + the US, useful for:
+
+- **Financial analysis & benchmarking** — Every record has real revenue, many have net income, assets, and equity
+- **Credit risk modeling** — All records have S.C.A.L.A. credit scores (50-100) and letter grades
+- **Lead generation & B2B prospecting** — Filter by country, sector, size, and financial health
+- **Market research** — Analyze business landscapes with actual financial data
+- **ML training** — High-quality labeled data for revenue prediction, credit scoring, sector classification
+
+## Schema
+
+| Column | Type | Description | Coverage |
+|--------|------|-------------|----------|
+| `name` | string | Company legal/trading name | 100% |
+| `city` | string | City / municipality | varies |
+| `country` | string | ISO 3166-1 alpha-2 country code | 100% |
+| `legal_form` | string | Legal entity type (SAS, SA, SRL, etc.) | varies |
+| `sector` | string | Industry sector code | varies |
+| `sector_desc` | string | Sector description (human-readable) | varies |
+| `status` | string | Company status (active, inactive, etc.) | varies |
+| `founded` | string | Year or date of incorporation | varies |
+| `employees` | integer | Number of employees | varies |
+| `revenue` | bigint | Annual revenue (local currency) | **100%** |
+| `net_income` | bigint | Net income (local currency) | varies |
+| `total_assets` | bigint | Total assets | varies |
+| `equity` | bigint | Shareholders' equity | varies |
+| `financial_year` | integer | Year of financial data | varies |
+| `score` | integer | S.C.A.L.A. credit score (50-100) | **100%** |
+| `grade` | string | Credit grade (A/B/C/D/E/F) | varies |
+| `source` | string | Data source identifier | 100% |
+
+Note: `tax_id` and `address` fields are excluded from this public sample for privacy. Available via the Score API.
+
+## Country Distribution
+
+| Country | Records | Avg Score | Avg Revenue | Max Revenue |
+|---------|---------|-----------|-------------|-------------|
+| FR | 400,000 | 53.5 | 18M | 214B |
+| NO | 200,000 | 60.4 | 60M | 941B |
+| IT | 200,000 | 77.0 | 20M | 190B |
+| PT | 80,000 | 64.2 | 2.4M | 29B |
+| SE | 50,000 | 65.0 | 17M | 26B |
+| BE | 30,000 | 65.0 | 28M | 92B |
+| DK | 27,000 | 65.1 | 270M | 425B |
+| CZ | 6,000 | 70.0 | 1B | 424B |
+| EE | 3,000 | 59.1 | 4.7M | 2.2B |
+| US | 2,000 | 80.3 | 12.9B | 717B |
+| LV | 1,000 | 76.3 | 82M | 1.4B |
+| ES | 500 | 58.4 | 492M | 62B |
+| FI | 500 | 54.2 | 169M | 25B |
+
+Revenue values are in local currency (EUR for most countries, NOK for Norway, SEK for Sweden, CZK for Czech Republic, USD for the US, DKK for Denmark).
+
+## Usage
+
+### Python (pandas)
+```python
+import pandas as pd
+df = pd.read_parquet("hf://datasets/Alessandro114/world-company-database/premium-1m-companies.parquet")
+print(df.shape)  # (1000000, 17)
+print(df['revenue'].describe())
+```
+
+### Python (DuckDB)
+```python
+import duckdb
+
+# Top 10 companies by revenue
+duckdb.sql("""
+    SELECT name, country, revenue, score, grade
+    FROM 'hf://datasets/Alessandro114/world-company-database/premium-1m-companies.parquet'
+    ORDER BY revenue DESC
+    LIMIT 10
+""").show()
+
+# Country breakdown
+duckdb.sql("""
+    SELECT country, COUNT(*) as companies, AVG(score) as avg_score,
+           AVG(revenue) as avg_revenue
+    FROM 'hf://datasets/Alessandro114/world-company-database/premium-1m-companies.parquet'
+    GROUP BY country ORDER BY companies DESC
+""").show()
+```
+
+### Python (datasets)
+```python
+from datasets import load_dataset
+ds = load_dataset("Alessandro114/world-company-database")
+```
+
+## Full Database Access
+
+This is a **premium 1M sample** from a database of **272+ million companies** across 265 countries.
+
+The full database contains 2.3M+ companies with financial data, and 272M+ total company records.
+
+For full access with advanced filtering, enrichment, and real-time updates:
+
+- **Score API**: [https://score.get-scala.com/api](https://score.get-scala.com/api) — RESTful API with country, sector, revenue, and employee filters
+- **Bulk exports**: Available for enterprise customers
+- **Custom enrichment**: Tax ID validation, financial data, credit scoring
+
+Built by [S.C.A.L.A.](https://get-scala.com) — the enterprise AI operating system.
+
+## License
+
+This dataset is released under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/).
+
+- **Non-commercial use**: Free with attribution
+- **Commercial use**: Requires API access — see [score.get-scala.com](https://score.get-scala.com)
+
+## Citation
+
+```bibtex
+@dataset{scala_score_premium_2026,
+  title={World Company Database - Premium 1M Sample with Revenue and Credit Scores},
+  author={S.C.A.L.A.},
+  year={2026},
+  url={https://huggingface.co/datasets/Alessandro114/world-company-database},
+  license={CC BY-NC 4.0}
+}
+```