> ## Documentation Index
> Fetch the complete documentation index at: https://knowledge.cloudquant.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Catalog

> Browse 70+ integrated financial, alternative, and economic datasets available through CloudQuant Data Liberator

# Data catalog - data integrations

CloudQuant Data Liberator integrates with over 70 data providers, offering a comprehensive catalog of financial, alternative, and economic datasets.

## Market & financial data

| Dataset                          | Description                     |
| -------------------------------- | ------------------------------- |
| **SpiderRock Options & Futures** | Options and futures market data |
| **CryptoQuote**                  | Cryptocurrency market data      |
| **S\&P Dow Jones Indices**       | Index data and analytics        |
| **Canari Options**               | Options analytics and data      |

## Alternative data

| Dataset                                 | Description                          |
| --------------------------------------- | ------------------------------------ |
| **Alexandria**                          | Earnings and news sentiment analysis |
| **BMLL Technologies**                   | Level 3 order book data              |
| **Exegy Hidden Order Flow**             | Hidden and dark pool order flow      |
| **GWI Audience Insight**                | Consumer audience analytics          |
| **Likefolio Twitter**                   | Social media sentiment from Twitter  |
| **Lunarcrush Crypto Sentiment**         | Cryptocurrency social sentiment      |
| **Smart Insider (Buybacks)**            | Corporate buyback intelligence       |
| **New Constructs (Earnings Anomalies)** | Earnings quality analytics           |
| **Precision Alpha**                     | Price prediction signals             |
| **Danel SmartScore**                    | Multi-factor scoring                 |

## Economic data

| Dataset                                    | Description                   |
| ------------------------------------------ | ----------------------------- |
| **FRED Release Series**                    | Federal Reserve Economic Data |
| **Bureau of Economic Analysis GDP**        | U.S. GDP data                 |
| **Bureau of Labor Statistics**             | Employment and labor data     |
| **U.S. Energy Information Administration** | Energy market data            |
| **EuroStat**                               | European economic statistics  |
| **CFTC Commitment of Traders**             | Futures positioning data      |

## Regulatory & reference data

| Dataset                        | Description                 |
| ------------------------------ | --------------------------- |
| **FINRA**                      | Financial regulatory data   |
| **SEC Filing Data**            | SEC filings and disclosures |
| **Regalytics Regulatory Data** | Regulatory intelligence     |

## Environmental & weather data

| Dataset              | Description                   |
| -------------------- | ----------------------------- |
| **Athenium Weather** | Weather analytics for trading |
| **CustomWeather**    | Custom weather data feeds     |
| **Ilika Weather**    | Weather data and forecasts    |

## Additional datasets

| Dataset                | Description                               |
| ---------------------- | ----------------------------------------- |
| **Linkup Jobs**        | Job market data                           |
| **Shipfix Shipping**   | Global shipping and freight data          |
| **ESG Data Providers** | Environmental, social, governance metrics |

<Note>
  Dataset availability depends on your subscription and entitlements. Use `liberator.datasets()` in Python to see which datasets you have access to. Contact CloudQuant to request access to additional datasets.
</Note>

## Accessing datasets

```python theme={null}
import liberator

# List all datasets you have access to
datasets = liberator.datasets()
print(datasets)

# Query a specific dataset
df = liberator.query(
    dataset="your_dataset_name",
    symbols=["AAPL"],
    as_of="2024-01-01",
    back_to="2023-01-01"
)
```

See the [Python Guide](/python-guide/dataset-access) for more details on discovering and querying datasets.