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

You're reading from   Kibana 8.x – A Quick Start Guide to Data Analysis Learn about data exploration, visualization, and dashboard building with Kibana

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781803232164
Length 198 pages
Edition 1st Edition
Tools
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Author (1):
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Krishna Shah Krishna Shah
Author Profile Icon Krishna Shah
Krishna Shah
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Table of Contents (17) Chapters Close

Preface 1. Part 1: Exploring Kibana
2. Chapter 1: Introduction to Kibana FREE CHAPTER 3. Chapter 2: Creating Data Views and Introducing Spaces 4. Chapter 3: Discovering the Data through Discover 5. Part 2: Visualizations in Kibana
6. Chapter 4: How About We Visualize? 7. Chapter 5: Powering Visualizations with Near Real-Time Updates 8. Part 3: Analytics on a Dashboard
9. Chapter 6: Data Analysis with Machine Learning 10. Chapter 7: Graph Visualization 11. Chapter 8: Finally, the Dashboard 12. Part 4: Querying on Kibana and Advanced Concepts
13. Chapter 9: ES|QL and Advanced Kibana Concepts 14. Chapter 10: Query DSL and Management through Kibana 15. Index 16. Other Books You May Enjoy

Creating a graph

The Graph API offers an alternative method for retrieving and summarizing data about the documents and keywords in your Elasticsearch index. Essentially, a graph represents a network of interconnected elements. In our context, this refers to a network of related keywords within the index.

Figure 7.1 – Vertices and edges in a graph in Kibana

Figure 7.1 – Vertices and edges in a graph in Kibana

The keywords that you wish to include in the graph are referred to as vertices. Each connection between two vertices represents a relationship. This relationship summarizes the documents that contain both of the terms associated with the vertices. The terms that have been indexed serve as the graph vertices. By utilizing Elasticsearch aggregations, the connections are generated dynamically. The API utilizes Elasticsearch relevance scoring to identify the most significant connections. This means that the same data structures and relevance-ranking tools used for text searches in Elasticsearch are...

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