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Mastering Elastic Stack

You're reading from   Mastering Elastic Stack Dive into data analysis with a pursuit of mastering ELK Stack on real-world scenarios.

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786460011
Length 526 pages
Edition 1st Edition
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Authors (2):
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Ravi Kumar Gupta Ravi Kumar Gupta
Author Profile Icon Ravi Kumar Gupta
Ravi Kumar Gupta
Yuvraj Gupta Yuvraj Gupta
Author Profile Icon Yuvraj Gupta
Yuvraj Gupta
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Toc

Table of Contents (13) Chapters Close

Preface 1. Elastic Stack Overview FREE CHAPTER 2. Stepping into Elasticsearch 3. Exploring Logstash and Its Plugins 4. Kibana Interface 5. Using Beats 6. Elastic Stack in Action 7. Customizing Elastic Stack 8. Elasticsearch APIs 9. X-Pack: Security and Monitoring 10. X-Pack: Alerting, Graph, and Reporting 11. Best Practices 12. Case Study-Meetup

Putting it all together

After learning about Elasticsearch, Logstash, and Kibana, let's use these components to create an end-to-end pipeline to parse data from Logstash to Elasticsearch and visualize it using Kibana. We will use a CSV file as input data, which will be used to analyze and create visualizations out of the data.

This will help us to quickly get started by using all the three components together to create an end-to-end pipeline. While using this example in this chapter, we assume that you have successfully installed Elasticsearch, Logstash, and Kibana as described in Chapter 1, Elastic Stack Overview.

Let's have a look at the input data.

Input data

We will be using the input data provided by United States Department of Agriculture Economic Research Service (USDA ERS), which is about educational attainment for the U.S and counties, 1970-2014. It provides information about the attainment of education, people who have less than a high school diploma, a high school...

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