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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

Product type Paperback

Published in Feb 2024

Publisher Packt

ISBN-13 9781803232164

Length 198 pages

Edition 1st Edition

Tools

Kibana

Concepts

Data Analysis

Author (1):

Krishna Shah

View More author details

Table of Contents (17) Chapters

Preface

1. Part 1: Exploring Kibana FREE CHAPTER

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

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16. Other Books You May Enjoy

Technical requirements

As per the basic requirements, we assume that you have data ingested in the cluster and that Elasticsearch and Kibana are 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 data sets, and then click on the Add data for Kibana_sample_data_ecommerce dataset. We shall be using this dataset for creating the visualization on Lens in this chapter.

The rest of the chapter is locked

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Authors (1)

Shah

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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