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Data access and preparation just became even more powerful and user friendly with KNIME v4.3

December 6, 2020
Data access and preparation just became even more powerful and user friendly with KNIME v4.3

KNIME’s winter release bolsters ETL, DL, Collaboration, and Deployment Monitoring in the enterprise.

Data access and preparation are inevitable basics for generating value from data. It’s a well known fact that most practitioners spend the majority of their time accessing, blending, or cleaning data. It’s also an open secret that KNIME is already very powerful in this discipline, and one of the reasons it's used in so many different industries. KNIME Analytics Platform offers native connectors to access most data sources and to perform whatever transformation needs to be done to data.

The release of KNIME Analytics Platform v4.3 is a big leap forward in making data access and data prep even more powerful and user friendly through a set of File Handling extensions. For example it’s now possible to easily read from and move (!) data over different file systems within the same workflow; a new node now makes table transformation much faster with an instant preview interface; and other new nodes drastically reduce the number of steps needed in a workflow. See the What's New page for more details.

Also, KNIME Server v4.12 comes with a big update and offers more capabilities for deployment. The highlights are:

Further advancements with the release:

  • Sharing and reusing work has become easier with updates in KNIME Hub. Check out here how you can manage your spaces and use KNIME Hub directly in KNIME Analytics Platform.
  • More functionality moved out of Labs: KNIME Deep Learning extensions (Keras and Tensorflow), and H2O, Tableau, and Salesforce integrations.
  • Easier to share and productionize workflows and components containing Python Scripting nodes

Pssst! Did you hear about the KNIME Columnar Table Backend extension? It’s not a new node and it’s not a piece of functionality, but an exciting new capability that will boost performance. It’s based on columnar representation and was just released into KNIME Labs. Read more here.

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