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

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

By : Shah
5 (3)
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Kibana 8.x – A Quick Start Guide to Data Analysis

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

5 (3)
By: 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)
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1
Part 1: Exploring Kibana
5
Part 2: Visualizations in Kibana
8
Part 3: Analytics on a Dashboard
12
Part 4: Querying on Kibana and Advanced Concepts

Exploring your data

Let us now start looking into how the data gets stored in the Elasticsearch cluster, which takes us to the concept of a document. Anything that we ingest in the cluster gets stored in the cluster as a document.

Elasticsearch – a document store

Before starting to understand how exploration of data can be done, Elasticsearch is called a distributed document store as it stores the data in the form of serialized JSON documents:

Figure 3.1 – An index with a collection of documents can be stored in Elasticsearch

Figure 3.1 – An index with a collection of documents can be stored in Elasticsearch

These JSON documents are distributed across all the nodes of the cluster. If we go into where this document is stored in an index, it would be a logical namespace called an Index. It can be thought of as a collection of JSON documents that has data stored in the form of key-value pairs that contain the data. See the following example:

 Figure 3.2 – A sample of a record of data

Figure 3.2 – A sample of a record of data

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