Book Image

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

By : Krishna Shah
Book Image

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

By: Krishna 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)
Free Chapter
Part 1: Exploring Kibana
Part 2: Visualizations in Kibana
Part 3: Analytics on a Dashboard
Part 4: Querying on Kibana and Advanced Concepts

Learning the ES|QL building blocks

ES|QL is built upon a foundation of robust query capabilities and an intuitive syntax that empowers users to interact effectively with Elasticsearch data. At its core, ES|QL leverages the Elasticsearch query DSL (short for Domain-Specific Language), providing a comprehensive set of commands to articulate complex queries. The language is designed for flexibility, allowing users to seamlessly navigate the intricate structure of Elasticsearch indices.

ES|QL’s architecture incorporates a deep understanding of Elasticsearch’s distributed nature, ensuring optimal performance across large-scale datasets. It embraces principles of scalability, enabling users to harness its capabilities in diverse and demanding environments. The development of ES|QL involves a collaborative effort from the Elasticsearch community, with continuous enhancements and updates being introduced to adapt to evolving user needs and accommodate the latest features of...