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Guided Visualization and Exploration

Guided visualizationGuided analyticsGuided explorationMachine learning automationJavaScript
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Feb 8, 2019 9:30 AM
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Guided exploration provides a data scientist with insights into data at hand. Any dataset can be used. The data are automatically cleaned by removing columns with constant values and by identifying the correct data types of the columns. The relationships between and within columns are calculated and shown by charts in an interactive composite view, where columns can also be flagged. By default the flagged columns are excluded from the dataset. If any other action for the flagged columns is preferred, a new action can be defined by replacing the Reference Column Filter node. Guided visualization provides a business analyst with the most appropriate visualizations according to how many columns are selected and what is the data type of these columns. At maximum 3 columns can be selected. The supported data types are numeric, String, and Date&Time. If the column types were not identified correctly, they can be converted manually. The appropriate visualizations are shown in an interactive composite view, where the charts can be customized. The customized charts are downloadable in SVG format. More charts can easily be added to the nested Wrapped Metanodes that contain the appropriate charts for the possible combinations of columns.

External resources

  • Guided Visualization and Exploration - KNIME Blog
  • KNIME Spring Summit 2019: Visualizing with Guided Analytics: for End Users and Experts
  • Principles of Guided Analytics
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Created with KNIME Analytics Platform version 4.4.0
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