Productionizing Data Science With the KNIME Server [Video]
A big data expert discusses the KNIM Server, and open source solution for data scientists, and how it can help teams work with data in production environments.
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Moving one step further to now put these data science applications into production, a number of requirements need to be taken into account.
First, multiple users working on the same projects might need to share files, opinions, and current work, in other words they might need to collaborate. A data science project rarely finishes with a trained model, the conclusive step is to deploy the model within a production application. Scalability in real world applications is another concern. Finally, all workflows, models, metanodes, and the data produced within the group need access rights, monitoring, versioning, and management.
The KNIME Server is a commercial product that extends the power of the KNIME Analytics Platform by improving the productivity of data science teams with collaborative, scalability, deployment, and management features, giving them more freedom and flexibility.
The following video describes the functionalities of KNIME Server, including:
- Collaboration among data science teams.
- Deployment options.
- Automated workflow execution.
- Access rights for workflows, metanodes, and data.
- Version control.
- Management and monitoring of jobs.
Published at DZone with permission of Vincenzo Tursi, DZone MVB. See the original article here.
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