Visualization Types

Flexera One offers a variety of visualization types to help you create insightful and interactive reports. These visualizations enable you to transform raw data into meaningful charts, graphs, and dashboards. Understanding how to use these visualizations is essential for effective data analysis and presentation.

Selecting the appropriate visualization depends on the type of data you have and the insights you want to convey. The following table lists some of the most used visualization types with their common usage.

Visualization Type

Usage

Bar and Column Charts

Ideal for comparing categories or showing changes over time.

Line and Area Charts

Best for trend analysis over a period.

Pie and Donut Charts

Useful for showing proportions and percentages of a whole.

Tables and Matrices

Suitable for displaying detailed data and summaries.

Cards

Great for highlighting key metrics.

Slicers

Used to filter data in reports interactively.

Maps

Perfect for geographical data representation.

Gauge and KPI

Excellent for performance metrics against a target.

Scatter and Bubble Charts

Effective for showing relationships between variables.

Treemap

Useful for hierarchical data visualization.

Waterfall Chart

Good for understanding the cumulative effect of sequential values.

Funnel Chart

Ideal for stages in a process or pipeline.

Tips for Creating Effective Visualizations

By understanding and utilizing visualization types, you can create compelling and insightful reports that effectively communicate your data story. Experiment with different visualizations to find the best fit for your data and reporting needs. Keep in mind the following tips to create effective visualizations:

Keep it Simple—Avoid cluttering the visualization with too many elements.
Use Appropriate Colors—Ensure that colors are meaningful and enhance readability.
Leverage Interactivity—Use slicers and filters to make your reports interactive.
Highlight Key Insights—Use cards, KPIs, and callouts to draw attention to important metrics.