WebPortal

Example for a Data Mining WebPortal

This workflow will allow the user to pick a data source and do some decision tree model learning on it. Valid data sources are an in-built SQLite database or the upload of either another SQLite DB file or a custom KNIME table file. The workflow will then analyse the table and offer the user too choose the target and independent variables. A (very simple) report will be generated and shown to the user.

Read file send as EMail

This workflow demos how a file can be upload to the KNIME Server and send via EMail. There are multiple sanity checks included. If no file was uploaded the user is asked to go back. If the sending of email fail another error message is shown. If everything works as expected a success message is output.

Read file send as EMail

 

Select most recent date and time cells

We here demonstrate how a date/time column can be filtered to contain only the last k month or week or days. On the webportal you chose the granularity and the number of those granularity you want to include in your analysis. Afterwards we filter them using the time difference (set to the selected granularity) and the rowfilter on the time difference value limited by the selected number of.

Showing an autogenerated time series line plot

This workflow shows the usage of quickforms to make a configurable user experience. In the first node, the user gets asked to provide a number of rows and features. Using this information, a table containing random time series is generated. On the second page, the user can chose which of the generated time series columns should be shown in the line plot contained on the third page of the webportal.

Visualize Scatterplot on file

This workflow demonstrates a usecase of the KNIME Webportal. Here a file can be uploaded and different parameters are chosen. The parameters provided here are the option that the first row of the table contains the column header and that the user can choose a column delimiter. Providing different parameters this workflow can be extended to read any kind of text based files.

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