Book Image

Kibana 8.x – A Quick Start Guide to Data Analysis

By : Krishna Shah
Book Image

Kibana 8.x – A Quick Start Guide to Data Analysis

By: Krishna Shah

Overview of this book

Unleash the full potential of Kibana—an indispensable tool for data analysts to seamlessly explore vast datasets, uncover key insights, identify trends and anomalies, and share results. This book guides you through its user-friendly interface, interactive visualizations, and robust features, including real-time data monitoring and advanced analytics, showing you how Kibana revolutionizes your approach to navigating and analyzing complex datasets. Starting with the foundational steps of installing, configuring, and running Kibana, this book progresses systematically to explain the search and data visualization capabilities for data stored in the Elasticsearch cluster. You’ll then delve into the practical details of creating data views and optimizing spaces to better organize the analysis environment. As you advance, you'll get to grips with using the discover interface and learn how to build different types of extensive visualizations using Lens. By the end of this book, you’ll have a complete understanding of how Kibana works, helping you leverage its capabilities to build an analytics and visualization solution from scratch for your data-driven use case.
Table of Contents (17 chapters)
Free Chapter
Part 1: Exploring Kibana
Part 2: Visualizations in Kibana
Part 3: Analytics on a Dashboard
Part 4: Querying on Kibana and Advanced Concepts


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.