Visualizaciones Comunitarias y Navegación en Looker Studio

Community visualizations in Looker Studio represent a powerful tool to elevate the visual quality of our dashboards and communicate data more effectively. While Looker Studio offers a robust set of native charts, sometimes we need more advanced or visually appealing options to convey our findings. In this article, we will explore how to leverage these third-party created visualizations, their benefits, and important considerations for implementing them correctly.

What are community visualizations in Looker Studio?

Community visualizations are advanced graphs developed by third parties that have been reviewed by Google and made available to all Looker Studio users. These visualizations significantly expand the possibilities of data representation, allowing us to create more interactive and visually appealing dashboards.

These tools are especially useful when:

• We need chart types that are not available in the native options.
• We want to incorporate animated elements to highlight information
• We are looking for more interactive visualizations to enhance the user experience
• We want to present complex relationships between data in a more intuitive way.

However, it is important to consider some aspects before implementing them. When using community visualizations, we share our data with external developers, which could represent a security risk if we are working with sensitive information. In addition, animations can affect dashboard performance, especially on devices with fewer resources.

Security and performance considerations

Before implementing community visualizations in our dashboards, we must take into account:

• Data security: all data used in these visualizations are shared with external developers. It is not recommended to use them with highly confidential information.
• Performance: Animations and interactive elements can make the dashboard more cumbersome. It is essential to test performance on different devices.
• Compatibility: Not all community visualizations are compatible with all data sources, so pre-testing is necessary.
• Stability: Some visualizations may disappear from the gallery if the developer removes them, which affects the long-term sustainability of our dashboards.

How to implement community visualizations in our dashboard?

Implementing these tools is relatively simple once we know the process. Let's take a step-by-step look at how to incorporate them into our work:

Access to the visualization gallery

1. Create a new page on the dashboard or use an existing one.
2. Find the community visualizations button (located next to the add chart button).
3. When clicked, a warning message about the use of external components will appear.
4. Select "See more" to access the full gallery of available visualizations.

It is important to note that some visualizations will appear as "unknown", indicating that they were previously available but have been removed from the gallery by the developer.

Practical example: Implementation of a Sankey diagram

Let's implement a Sankey diagram, a useful visualization to show flows and relationships between categories:

1. Search for "Sankey" in the visualization gallery.
2. Click on "Use" and accept the terms and conditions
3. Configure the dimensions and metrics:
   • Select "payment_means_2" as the first dimension.
   • Add "branch_2" as second dimension

This type of visualization allows us to analyze how payment methods relate to each branch, identifying patterns of preference among users.

Customizing the style

Once the visualization is implemented, we can customize it:

- Add labels to the nodes to identify each element- Adjust the color of the text to improve contrast- Modify the colors of the elements to highlight relevant information- Adjust the opacity according to our preferences- Add shadows to give depth to the visualization.

Customization is key for these visualizations to integrate correctly with the overall design of our dashboard and communicate information effectively.

Implementing interactive filters

To make our dashboard even more interactive, we can implement advanced filters such as the "Range Slider":

1. Search for "Range Slider" in the visualization gallery.
2. Configure a continuous metric (such as "total_sales")
3. Activate the multi-filter function in the "Interactive Charts" section.

This type of filter allows us to analyze how the relationships in our data change according to different ranges of values. For example, we can observe whether the preference for certain means of payment varies according to the amount of the purchase.

When to use community visualizations?

Community visualizations are particularly useful in certain scenarios:

• Executive presentations: When we need to make a visual impact and communicate complex findings in an intuitive way.
• Complex relationship analysis: To visualize connections between multiple variables that would be difficult to represent with standard graphs
• Public dashboards: In situations where user experience and visual appeal are a priority.
• Exploratory analysis: When we want to provide users with interactive tools to explore the data for themselves.

However, for environments with highly sensitive data or where stability and performance are critical, it is preferable to stick with Looker Studio's native visualizations.

Community visualizations represent an excellent way to elevate our dashboards to a professional level, allowing us to communicate insights in a more effective and engaging way. Always remember to verify security, performance and compatibility before deploying them in production environments. We encourage you to explore the full gallery of visualizations and share your favorite findings to further enrich our data analytics community.