Please visit the page about Reports for information how reports can be created and how they work. This helps to understand the example on this page.

Reports allow the results of the Data Scientists to be visually appealingly converted into an easy-to-understand presentation format and are based directly on the data of the workflows and therefore dynamically updates themselves every time the related workflow is executed.
Due to the modular structure of the grid and many different container types every logic can be covered, so that there are nearly no boundaries in visualizing your data properly.

This is an example of a report from viewer perspective:

When opening the very same report in edit mode we see how the modular container logic for building reports works:
There are many different container types mixed together to build up the report like for example:
  1. Pages container: Enables to link many report pages over tabs.
  2. Filter container: Filters all visualization container on all pages on default. Can be adjusted in its settings.
  3. Auxiliary container: Offers an "word a like" text box to add text and links to the report.
  4. Visualization container - Bar chart: Possibility to visualize the data.
  5. Visualization container - Table: Possibility to visualize the data.
  6. Visualization container -  Line chart: Possibility to visualize the data.
  7. Visualization Container - Pie chart: Possibility to visualize the data.


Every container header follows one simple logic:

  1. Title of the Container and the chart that is displayed in view mode. 
  2. Settings opens up a subpage for the configuration of the container on the right sight of the window.
  3. Deletes the container
  4. Mark allows to mark the container in order to apply changes on many containers at once
  5. Moves to container in a drag-and-drop style over the grid


 


When opening the settings a subpage slides in on the right side of the window which allows to apply changes to the container and the graph:


In this example a visualization container is selected.

  1. The visualization/chart type is selected here.
  2. We can add custom SQL.
  3. Decide which filter should get a synchronization when the data of the underlying table changes.
  4. Have to set which column of the underlying table provides the data for the x axis.
  5. Have to set which column of the underlying table provides the data for the y axis. (Can be more fields, depending of the visualization type that is selected (1).
  6. Here a description is set that is shown when hovering over the graph.
  7. Here Formation on the Axis in terms of style can be done.
  8. Axis Labels can be changed here.
  9. The size of the label including the steps between the values can be adjusted.
  10. Here one can choose between No-, absolute and percentage stacking.
  11. A logarithmic scale on the graph can be applied here.
  12. Rules on data formatting for the whole data of this container can be set here.
  13. If this slider is green the graph is directly updated so that the changes are visualized right away.