Data Visualization with Different Chart Types

Learn how to visualize your data using line and column charts, mixed charts, tables and waterfalls. 

To present your data you can choose based on a set of chart types. This article will give you an overview of the available chart types and tries to answer in what situation to use which chart types. To learn more about how to configure a chart, please read the article about how to display data using charts.

  • Line: A chart that displays its data series as connected lines. Line charts are useful to see the development or trends of chosen key figures.
  • Column: A column chart displays data using vertical bars. Multiple data series can be displayed next to each other using different colours. They are useful to compare different key figures in the same dimensionality, e.g. you can use it to compare the profit across different scenarios and years.
  • Bar Chart: A rotated column chart. 
  • stacked column chart displays its data using vertical bars and stacks the bars on top of each other if multiple data series are displayed. You can use them to highlight the individual parts contained in a key figure, for example the sales volume of each product and its share to the total sales volume.
  • Mixed charts are a combination between a stacked column and a line chart. By default, data series are displayed as stacked vertical bars, but it is possible to configure single data series to be displayed as a line. You can use mixed charts to display the relations between multiple key figures.

  • Tables allow to display data in a tabular format and flexibly selecting dimensions for the rows and columns. In tables you can display a lot of information from different key figures and its sub figures across multiple many dimensions and compare different scenarios, e.g. you can build profit and loss statements, cash-flow statements and more.
  • waterfall chart displays a transition between values, it can be e.g. used to create a profit bridge that explains how the profit developed was from one year to the next or to create an assumption bridge that explains a simulation scenario by adding up the effects of all assumptions.

  • The assumption bridge displays the effect of all assumptions to a key figure. There you can show the effect of the whole assumptions or the effect of each line item inside the assumptions.

  • The raw data table displays unaggregated data for a selected node with all its available dimensions. It can be used to display the full information behind a single node. It's the same table you get, if you choose 'preview data' on a node in the model editor.
  • KPI chart can be used to display an important single value. Optionally values for multiple scenarios can be displayed and compared.
  • Model tree charts show the graphical value driver structure of the underlying model and allows to display values for multiple scenarios inside of the nodes. They are very useful to understand how data flows through a model and impacts top KPIs.
  • Dimension tree charts show a graphical representation of the hierarchy of a selected dimensions and allows to visually see how values for a scenario a calculated and aggregated for a dimensions.

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