KNIME for MLOps and IT

Securely deploy, manage and scale analytics with a single installation while ensuring enterprise-grade security and governance

  • Test, validate, deploy, and monitor models in one single end-to-end data science platform

  • Ensure data security and governance with centralized administration and access controls

  • Create dynamic pricing strategies to respond to competitor and seasonal patterns

  • Deploy analyses on-premises or in the cloud with a single install and no limits on scaling

How Truata anonymizes credit card data to deliver customer insights
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How Netzeffekt automated cross-channel data harmonization
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How ZF Group optimized end-of-line testing with KNIME
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Why KNIME for MLOps and IT

Safely deploy and monitor models from one single place

Validate workflows before they are deployed. Monitor the results of deployed workflows and update and re-deploy them, if required to keep up with changing data and conditions. Create a training workflow that can be triggered to recreate or retrain a model for a production workflow. Keep track of what happens to your models with a log of each state of the productionization process.

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Ensure adherence to best practices

Infuse best practices into automated or semi-automated processes to test, validate, deploy and monitor models, decreasing bottlenecks and manual work for administrators. Get a framework to separate dev, testing and production environments. Use the same framework to define and customize the testing, validation and deployment stages and monitor the production process to define quality measures.

Meet enterprise needs while ensuring data security and governance

Provide timely access to data and insights while mitigating risk through centralized access control, user rights management, and encryption. Ensure reproducibility with governance features like versioning, meta-data mapping, auto-documentation, logging, and monitoring. Avoid unintended changes with rollback, and granular permissions around workflows.

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Secure productionization at scale

Support an unlimited number of users, running any number of models, which are then deployed to any number of consumers with a single installation, using KNIME Business Hub’s scalable, cloud-native architecture. Enable teams to act independently and manage their own resources within parameters specified by IT. Get high scalability with minimal burden on IT while retaining centralized control.

Community-driven innovation

Stay on the bleeding edge of data science with KNIME’s open source approach that provides integrations to all popular machine learning libraries and 300+ connectors to data sources. Avoid vendor lock-in with the extensibility of KNIME and get the ability to adapt to changing business needs through an open platform.

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Recommended Resources

How to Choose a Data Analytics Platform
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Continuous Delivery of Data Science
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Model Monitoring in a Data Science Context
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