KNIME Integrated Deployment

The KNIME Data Science Life Cycle

Closing the gap between data science creation and putting results into production

The end to end data science process traditionally starts with raw data and ends with the creation of a model. Moving that model into daily production requires considerable extra work, causing many businesses to stumble at the gap between having created a model and putting it into production. Integrated Deployment allows not just the 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. Using KNIME Integrated Deployment, organizations can replicate the process repeatedly with ease to maintain model performance.

The benefits

Time savings

Save time and free up both data science and model operations resources.

knime_icons_rz Fewer errors

Reduce the error risk associated with moving from model creation to deploying production processes.

Increased compliance

Capture and store both creation and production processes = full support of governance and compliance reporting.

Optimized processes

Optimize the updating of productions processes automatically.

How it works

A workflow is created to generate an optimal model. The Integrated Deployment nodes allow the data scientist to capture the parts of the workflow needed for running in a production environment, the model or library itself as well as the data preparation. These captured subsets are saved automatically as workflows with all the relevant settings and transformations. There is no limitation in this identification process - it can be as simple or as complex as required.

KNIME Integrated Deployment Abstract Workflow

Learn more about our approach to productionizing data science in CEO & co-founder, Michael Berthold’s article for InfoWorld

KNIME Business Hub

With KNIME Business Hub in production, the captured workflows can be automatically referenced and reused. Organizations with many production models benefit from being able to take the optimized creation workflows and use them in a scheduled or triggered environment. When new models are required in production, the same KNIME Business Hub setup can rerun the captured workflows automatically, delivering newly updated and automated production workflows to the business.

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Read about Integrated Deployment

Dive deeper into the challenges around productionizing data science in these articles.

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