Custom Visualizations in Dynatrace

Introduction

Custom visualizations allow users to create tailored graphical representations of their data within Dynatrace. This tutorial will cover the fundamentals of creating custom visualizations, including the types of visualizations available, how to design them, and the necessary steps to implement them in Dynatrace.

Understanding Custom Visualizations

Custom visualizations are essential for users who need specific insights from their data that standard visualizations may not provide. They facilitate better decision-making by allowing users to represent data in a way that best suits their analytical needs.

Examples of custom visualizations include heat maps, tailored line graphs, and specific KPI dashboards that focus on user-defined metrics.

Types of Custom Visualizations

In Dynatrace, you can create several types of custom visualizations. Some of the common types include:

• Bar Charts
• Line Graphs
• Pie Charts
• Heat Maps
• Custom Dashboards

Creating a Custom Visualization

To create a custom visualization in Dynatrace, follow these steps:

1. Log in to your Dynatrace account.
2. Navigate to the Dashboards section.
3. Select Create dashboard to start a new dashboard.
4. Choose the type of visualization you want to create from the available options.
5. Configure your visualization settings by selecting the data sources and metrics you wish to display.
6. Adjust the layout and appearance to fit your analytical needs.
7. Save your dashboard and share it with your team if necessary.

Example: Creating a Custom Line Graph

Here’s a step-by-step example of how to create a custom line graph:

Best Practices for Custom Visualizations

When creating custom visualizations, consider the following best practices:

• Focus on clarity: Ensure that your visualizations are easy to understand.
• Use appropriate colors: Choose colors that are distinguishable and meaningful.
• Limit data overload: Avoid cluttering your visualizations with too much information.
• Test your visualizations: Ensure they provide the insights you need before sharing them.

Conclusion

Custom visualizations in Dynatrace empower users to gain deeper insights into their data. By following the steps outlined in this tutorial, you can create effective visual representations tailored to your specific analytical objectives. Experiment with different types of visualizations and configurations to find what works best for your needs.