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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

Product type Book

Published in Feb 2024

Publisher Packt

ISBN-13 9781803232164

Pages 198 pages

Edition 1st Edition

Languages

Concepts

Data Engineering

Author (1):

Krishna Shah

Table of Contents (17) Chapters

Preface

1. Part 1: Exploring Kibana

2. Chapter 1: Introduction to Kibana

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

Why subscribe?

16. Other Books You May Enjoy

Summary

In this chapter, we explored how the graph analytics features offer a user-friendly yet robust graph exploration API, along with an interactive graph visualization app designed for Kibana. Best of all, these features seamlessly integrate with existing Elasticsearch indices, eliminating the need for any additional data storage. We learned how to create graph visualization from existing data views as well as reviewing key points to note when it comes to performance tuning and troubleshooting graph visualization.

If you’re waiting to learn something really new and super interesting, the next chapter will do that. ES|QL is here to help us get the best out of the search functionality of Kibana. We will also learn about some advanced concepts, such as scripted fields, in Kibana.

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Authors (1)

Krishna Shah

Krishna Shah is a data architect from Melbourne, Australia with 9+ years of experience, and she knows how to make data work. She's been an official trainer for Elasticsearch and Kibana, crafting the courses that empower people to unlock the secrets of data. Prior to that, she worked for a start-up in India as the data engineer behind building and maintaining data engineering pipelines, then transforming that raw information into stunning visuals and insights using Kibana and other data engineering technologies. Today, she's an advocate, a mentor, and a bridge-builder, inviting everyone to find their own rhythm in the data's dance. Whether you're a novice or seasoned analyst, brace yourself for her infectious enthusiasm and knack for making the driest of datasets sing!

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