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

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

By : Shah
5 (3)
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Kibana 8.x – A Quick Start Guide to Data Analysis

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

5 (3)
By: Shah

Overview of this book

Unleash the full potential of Kibana—an indispensable tool for data analysts to seamlessly explore vast datasets, uncover key insights, identify trends and anomalies, and share results. This book guides you through its user-friendly interface, interactive visualizations, and robust features, including real-time data monitoring and advanced analytics, showing you how Kibana revolutionizes your approach to navigating and analyzing complex datasets. Starting with the foundational steps of installing, configuring, and running Kibana, this book progresses systematically to explain the search and data visualization capabilities for data stored in the Elasticsearch cluster. You’ll then delve into the practical details of creating data views and optimizing spaces to better organize the analysis environment. As you advance, you'll get to grips with using the discover interface and learn how to build different types of extensive visualizations using Lens. By the end of this book, you’ll have a complete understanding of how Kibana works, helping you leverage its capabilities to build an analytics and visualization solution from scratch for your data-driven use case.
Table of Contents (17 chapters)
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1
Part 1: Exploring Kibana
5
Part 2: Visualizations in Kibana
8
Part 3: Analytics on a Dashboard
12
Part 4: Querying on Kibana and Advanced Concepts

Deep diving into the backend of visualizations in Kibana

A visualization is simple to understand and create because, as we all know, it is on the frontend. But what powers up this visualization on Kibana from the backend is your aggregations. Elasticsearch aggregations help us to analyze our data with metrics or statistics, which require certain calculations to be done in the backend. So, you may have questions in your use case:

  • Who are the most popular customers in my e-commerce dataset?
  • What category of sales made the most profit in my business?
  • What is the minimum runtime per day for my log data?
  • What is the unique number of countries that are contributing to my geographical data?

All these questions can be answered by implementing various aggregations on Elasticsearch. The aggregations can be divided into key categories:

  • Metric aggregations: Any problem statement that requires Elasticsearch to perform analytics as a mathematical formula on numeric...

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