Creating a visualization

Data can be of many different kinds. Therefore, several types of visualizations are offered to present it in a relevant way. To create visualizations, either use Recommendations or create the visualizations from scratch.

Using Recommendations

When adding data and selecting data columns of interest, you are presented with recommended visualizations. Simply choose visualizations you find suitable, and use them as they are, or adjust them to suit your needs.

Creating visualization from scratch

Another option is to create visualizations from the very beginning and make your own settings. To learn how to set up the different visualizations from scratch, click the links.

Creating a table
The table visualization presents the details of the data. The individual values are arranged in columns and rows.
Creating a cross table
Cross tables are used to summarize large amounts of data, and then present the result in a structured table format.
Creating a bar chart
In a bar chart, you can compare values for different categories in your data.
Creating a line chart
A line chart is used for showing trends, and in most cases trends over time. It can also be used for discerning certain patterns.
Creating a combination chart
In a combination chart, you have the option to display both bars and lines in a single visualization. Because of the overlay effect, lines are drawn on top of the bars, it is easy to compare values for different columns or categories in your data. Trends can be identified, and you can spot deviations directly.
Creating a pie chart
A pie chart is a circle graph that is divided into sectors. It is used to compare values for different categories in your data on a relative basis. Each pie sector represents a specific category, and its size the category's contribution to the whole value, expressed as a percentage. The values are usually sums.
Creating a scatter plot
In a scatter plot, markers are displayed in a two-dimensional coordinate system. It is useful for getting an overview of how your data is distributed across two dimensions.
Creating a map chart with markers
In a map chart with markers, data associated with locations is represented by markers placed in a geographical context.
Creating a map chart with colored regions
In a map chart with colored regions, colors represent data associated with geographical regions. The regions, also called features, can be for example countries, provinces or postal code areas. The entire shape of a region is colored, and it is automatically placed in its geographical context.
Creating a treemap
A treemap is used for displaying huge amounts of data that can be structured hierarchically (tree-structured). It presents the data using differently sized and colored rectangles.
Creating a parallel coordinate plot
A parallel coordinate plot is used to compare data values which are of completely different types or magnitudes within a single visualization. The values are normalized and then presented as points on a line with one point per data column. The visualization is useful also for examining patterns.
Creating a histogram
In a histogram, you can show the distribution of numerical data. The entire range of the numerical values is divided into equal intervals on the Category axis, and for each interval, it is indicated on the Value axis how many individual data values that fall within it.