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Learning Kibana 5.0

You're reading from Learning Kibana 5.0 Exploit the visualization capabilities of Kibana and build powerful interactive dashboards

Product type Paperback

Published in Feb 2017

Publisher Packt

ISBN-13 9781786463005

Length 284 pages

Edition 1st Edition

Languages

Java

Tools

Elasticsearch

Concepts

Data Visualization

Author (1):

Bahaaldine Azarmi

View More author details

Table of Contents (10) Chapters

Preface

1. Introduction to Data-Driven Architecture

2. Installing and Setting Up Kibana 5.0 FREE CHAPTER

3. Business Analytics with Kibana 5.0

4. Logging Analytics with Kibana 5.0

5. Metric Analytics with Metricbeat and Kibana 5.0

6. Graph Exploration in Kibana

7. Customizing Kibana 5.0 Timelion

8. Anomaly Detection in Kibana 5.0

9. Creating a Custom Plugin for Kibana 5.0

Chapter 6. Graph Exploration in Kibana

In earlier chapters, we went through a logging and metric analytics scenario that mainly leveraged the aggregation API in Elasticsearch.

But what if the need was not necessarily to highlight the KPI in the data, but rather to show the interconnection of data based on relevancy? This is where Elastic Graph comes into play. Graph is an X-Pack plugin that allows us to reveal significant connections between data indexed in Elasticsearch.

Elastic Graph comes with a new API in Elasticsearch and a new UI in Kibana, which offers a totally different approach to exploring data: rather than addressing data through the angle of value aggregation and narrowing them down by filtering to discover patterns, Graph allows you to play with vertices (the terms indexed in Elasticsearch) and connections (how many documents share the terms in the index) and map out significant relations.

In this chapter, we'll learn the following concepts of the Elastic...

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Authors (1)

Bahaaldine Azarmi

Bahaaldine Azarmi

Bahaaldine Azarmi, or Baha for short, is the head of solutions architecture in the EMEA South region at Elastic. Prior to this position, Baha co-founded ReachFive, a marketing data platform focused on user behavior and social analytics. He has also worked for a number of different software vendors, including Talend and Oracle, where he held positions as a solutions architect and architect. Prior to Machine Learning with the Elastic Stack, Baha authored books including Learning Kibana 5.0, Scalable Big Data Architecture, and Talend for Big Data. He is based in Paris and holds an MSc in computer science from Polytech'Paris.

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