Visualizations
There are a range of visualizations available to help you visualize your data in analytic apps.
The following visualization are available:
-
Bar chart: Visualize differences in measures over one or more dimensions, arranged as a series of bars with varying height. Can be displayed in vertical or horizontal format, and with grouped, stacked, or butterfly presentation. -
Box plot: The box plot is suitable for comparing range and distribution for groups of numerical data, illustrated by a box with whiskers, and a center line in the middle. -
Bullet chart: Bullet charts can be used to visualize and compare performance of a measure to a target value and to a qualitative scale, such as poor, average, and good. -
Combo chart: The combo chart combines bars and lines in the same chart. The bars and lines have different axes to enable comparing percentages and sums. Available as horizontal or vertical combo chart. -
Distribution plot: The distribution plot is suitable for comparing range and distribution for groups of numerical data. Data is plotted as value points along an axis. -
Filter pane: The filter pane allows you to control what data that is shown in the visualizations on a sheet. A filter pane can filter the data of several dimensions at once. -
Funnel chart: A funnel chart is a visual representation of the connected stages of a linear process. -
Gauge: The gauge is used to display the value of a single measure, lacking dimensions. -
Grid chart: A chart that displays comparative data and with the values represented as colors. -
Histogram: The histogram is suitable for visualizing distribution of numerical data over a continuous interval, or a certain time period. The data is divided into bins. -
KPI: The KPI is used to present central performance figures. You can add a link to a sheet. -
Line chart: The line chart displays data lines between values. Line charts are often used to visualize a trend in data over intervals of time. Can also be presented as an 
Area line chart. -
Map: The map is used to combine geospatial data and measure values, such as the sales for a region or a store. -
Mekko chart: The mekko chart compares a group while comparing category items contained within these groups. -
Org chart: Creates an organization chart with a tree structure. -
Pivot: Pivot presents dimensions and measures as rows and columns of a pivot table. The pivot table allows you to analyze data in multiple dimensions at a time. The data in a pivot table may be grouped based on a combination of the dimensions, and partial sums can be shown. -
Pivot table: The pivot table presents dimensions and measures as rows and columns of a table. The pivot table allows you to analyze data in multiple dimensions at a time. The data in a pivot table may be grouped based on a combination of the dimensions, and partial sums can be shown.
-
Sankey chart: A flow chart diagram chart visually emphasizing major transfers or flows within defined system boundaries. -
Scatter plot: The scatter plot presents values from two measures. This is useful when you want to show data where each instance has two numbers, for example, country (population and population growth). An optional third measure can be used and is then reflected in the size of the bubbles. When showing large data sets colors will be used instead of bubble size to represent the measure size. -
Straight table: The straight table allows you to present tabular data for detailed analysis. You can apply pagination to simplify consumption of large data volumes. You can also allow users to add and remove columns temporarily during analysis, using an enhanced chart exploration experience. -
Treemap: The treemap shows hierarchical data. A treemap can show a large number of values simultaneously within a limited space. -
Waterfall chart: The waterfall chart illustrates how an initial value is affected by intermediate positive and negative values. -
Write table: Use the write table to allow users to make changes in editable columns during data analysis.