It allows not just a model but all of its associated preparation and post- process steps to be identified and automatically reused in production with no changes or manual work required. From within the Knime platform, organizations can replicate the process repeatedly with ease to maintain model performance. The platform is also said to dramatically reduce the risk of errors that can occur when moving from creating a model to deploying a complete production process based on that model. Another benefit is that good governance and compliance reporting for such topics as GDPR and CCPR are fully supported since the entire creation and production processes are captured and stored in self-documenting workflows.
Integrated Deployment is significant because virtually all business topics that use decision science are affected by this gap. For example, a mobile provider might develop a model to predict whether customers will renew their contracts. This model relies on call transaction data, payment data, and information about support provided. The iterative model creation process discovers that the best model is made by combining 15 pieces of data. Nine of these pieces do not exist in the raw data but were created using both traditional mathematics as well as advanced techniques. The model method itself has had settings tuned for best performance.
Until now, the process of moving that model into production and applying it to new customers has required manual replication of the exact data creation and model settings to ensure that the model could be usable in production. With Knime Integrated Deployment, however, the created model as well as all required steps and settings are automatically captured and packaged so that the entire production process is, for the first time, instantly available for production use.