Workflow-based data analysis with KNIME
Data analysts like to use flexible scripting languages such as R or Python that come with large ecosystems of libraries and extensions. But many users don't want to have to write and debug their own custom programs just to analyze data.
Visual workflows offer a different approach. You can use visual workflows to break down the analysis processes into modular, sequential steps. Each step is symbolized by a graphic element called a node. Each node performs an action, which might be a calculation, a formatting function, or another step related to data analysis and manipulation. By linking the nodes on the screen, users can create workflows for complex investigations of the data – without producing any code.
Visual workflows are the central element of the KNIME Analytics Platform. In the KNIME environment, a workflow is a graph with nodes showing a series of sequential steps for processing and analyzing the data. The user defines a pathway for the data by connecting the output of one node to the input of another node. A type system ensures that you can only connect compatible output and input. Real programming code is only necessary if you want to integrate KNIME with R or Python – or if you want to develop your own modules.
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