# Lumber price forecasting with Ready Signal

> Lumber price forecasting with Ready Signal - Use Ready Signal to add external control data, such as
> census and weather data, to improve time series predictions.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-05-06T18:17:09.585968+00:00` (UTC).

## Primary page

- [Lumber price forecasting with Ready Signal](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/time-series/ready-signal.html): Full documentation for this topic (HTML).

## Related documentation

- [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page.
- [Developer learning](https://docs.datarobot.com/en/docs/api/dev-learning/index.html): Linked from this page.
- [AI accelerators](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/index.html): Linked from this page.
- [Time series and specific use cases](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/time-series/index.html): Linked from this page.

## Documentation content

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/blob/main/advanced_ml_and_api_approaches/data_enrichment_ready_signal_ts/DataRobot_RXA.ipynb)

In this accelerator, you will explore how to bring external data from Ready Signal to help augment your time series forecasting accuracy.

Ready Signal is an AI-powered data platform that provides access to over 500 normalized, aggregated, and automatically updated data sources for predictive modeling, experimentation, business intelligence, and other data enrichment needs. The data catalog includes micro/macro-economic indicators, labor statistics, demographics, weather, and more. Its AI recommendation engine and auto feature engineering capabilities make it easy to integrate with existing data pipelines and analytics tooling, accelerating and enhancing how relevant third-party data is leveraged.

Here, DataRobot provides an example of predicting lumber price combined with the most relevant external data automatically identified by ReadySignal based on correlation with the target variable. The workflow can be applied to any time series forecasting project.