Enhancing Forecast Accuracy with DataRobot and Ready Signal’s External Feature Store 

Forecast Accuracy

Forecasting accuracy is a critical element in decision-making processes for any business. In this video, DataRobot showcases the enhanced power of its AI platform when coupled with Ready Signal’s external feature store. The result? A staggering 13% improvement in forecast accuracy in minutes. This video illustrates the immense potential of integrating external data seamlessly into predictive models. 

The Power of Integration:  

DataRobot’s AI Platform is an industry leader for its ability to create, deploy, and maintain high impact forecast models. Ready Signal’s external data platform seamlessly integrates with its modeling engine, acting as a Feature Store with over 500 normalized, aggregated, and automatically updated external data sets. 

Watch the Demo: 

Experience the integration for yourself by watching the demo below:

The Demonstration:  

The video walks through a practical example of leveraging Ready Signal’s external data in conjunction with DataRobot’s time series capabilities. The presenter demonstrates a no-code approach, emphasizing the ease with which users can integrate external data into their forecasting models. 

Step-by-Step Process: 

  1. Accessing External Data: The presenter logs into Ready Signal and accesses a signal with 34 external features, including economic indicators, weather, and demographic data. 
  1. Data Extraction: The external data is easily extracted as a flat file, enabling users to seamlessly blend it with their existing internal data. (also available via API) 
  1. Data Integration: The presenter illustrates the process of joining the external data from Ready Signal with the original dataset, adding 34 additional columns for a more comprehensive set of features. 
  1. Model Training: Two sets of models are trained – one with only the original private data and another with the additional external data from Ready Signal. 
  1. Results Analysis: DataRobot’s automated processes yield models with varying levels of accuracy. The presenter compares the model’s performance, revealing a remarkable 13% improvement in Mean Absolute Scaled Error (MASE) when external data is integrated. 

Key Findings:  

The video highlights key findings from the analysis, displaying the impact of external data on forecast accuracy. Notable contributors to the improvement include weighted influenza-like illness national summary, actual rainfall, and foreign exchange rates. 

DataRobot and Ready Signal: Enhance Forecast Accuracy

The collaboration between DataRobot and Ready Signal proves to be a game-changer in the realm of forecasting. By seamlessly integrating external features, users can significantly enhance the accuracy of their models, enabling more informed decision-making. 

Stay Connected: For further insights and updates, stay connected with DataRobot through their Blog and Community

In a world where data-driven decisions are paramount, the collaboration between DataRobot and Ready Signal provides a powerful solution for organizations seeking to elevate their forecasting capabilities. 

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