How About We Visualize?

The best way to clearly understand what your data is all about is to visualize it. And everyone appreciates a visually stunning Kibana dashboard, with its assortment of graphs and representations that display real-time data. From simple pie charts or vertical bar graphs to interactive map visualizations, the ability to manipulate and analyze data is what Kibana excels at. But before you can enjoy the beauty of a well-designed Kibana dashboard, several essential milestones must be taken.

While experienced Kibana users may breeze through these steps effortlessly, for most users, they can prove to be quite challenging. It requires both experience and a deep understanding of your dataset and the features such as the Visualize library in Kibana. This chapter aims to assist those who are struggling with their initial attempts at visualizing data in Kibana. It is time to learn to effectively visualize data using this powerful functionality of creating a specific...

Technical requirements

As per the basic requirement, we assume that you have data ingested in the cluster and that Kibana is set up on the nodes of (any) environment (cloud or local).

Once Kibana is up and running, we can navigate to Kibana home page and click on Try sample data | Other sample datasets, then click on Add data for Kibana_sample_data_ecommerce dataset.

We will be using this dataset for creating a visualization on Lens in this chapter.

Exploring Lens visualizations

If you’re a newbie in the field of visualizing data, then you have come to the right place! If you are not sure how you wish to get started on creating a visualization or which type of visualization you wish to use to represent your data, Lens is a great way to simply drag and drop the fields you want to build a graph on. And voilà – it will create a vertical bar graph to start with. We can change the type of the graph to any other representation that we prefer later.

The ease and flexibility of the drag-and-drop experience is what makes the Lens visualization one sure spot for pretty much everything that one wishes to do with representing data in the form of a visualization.

Let us look at the process of creating a sample Lens visualization process step by step:

1. Get to know the Lens page; there is a name for everything on the interface, as shown in the following screenshot:

Figure 4.1 –...

Deep diving into the backend of visualizations in Kibana

A visualization is simple to understand and create because, as we all know, it is on the frontend. But what powers up this visualization on Kibana from the backend is your aggregations. Elasticsearch aggregations help us to analyze our data with metrics or statistics, which require certain calculations to be done in the backend. So, you may have questions in your use case:

• Who are the most popular customers in my e-commerce dataset?
• What category of sales made the most profit in my business?
• What is the minimum runtime per day for my log data?
• What is the unique number of countries that are contributing to my geographical data?

All these questions can be answered by implementing various aggregations on Elasticsearch. The aggregations can be divided into key categories:

• Metric aggregations: Any problem statement that requires Elasticsearch to perform analytics as a mathematical formula on numeric...

Understanding Canvas, Maps, and Markdown visualizations

We have seen visualizations where we had a definitive purpose in mind with respect to what we’d like to do with the analysis. However, when we have intricately custom use cases such as adding our own images to highlight our company/customer information, we would need to create a Canvas visualization. A Canvas visualization is very similar to a literal white canvas that makes you, the artist, create/draw/add anything you like and make it interesting to present.

If you need to look at data points coming from different parts of the world, then we might need a map, which lets us create a visualization on a world map to display data in the form of different symbols. To add anything to the dashboard that is related to text, Markdown is a great visualization to start with. Let’s start looking at each one of them step by step.

Building Canvas visualizations

Canvas is a powerful tool for visualizing and presenting...

Summary

In this chapter, we explored and deep-dived into how different types of visualizations can be created and saved to a library or added to a dashboard. We explored a Lens visualization as one sure solution to many problems, with the help of two types of aggregations: metric and bucket aggregations, which work for us in the backend to retrieve the data. We also studied how geospatial fields that have geographical coordinates mapped to them in the data can be used to create a Maps visualization to pictorially display data on a world map. Also, we saw that Canvas, on the other hand, helps us create every type of view that could be part of a completely custom-defined requirement for a use case.

In the upcoming chapter, we will see how we utilize these visualizations to create a view called a dashboard that will help us connect a lot of dots in establishing important relationships within our data in the cluster.