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 about Query DSL

Query DSL, as we discussed earlier, is a JSON-based DSL that empowers you to construct intricate search queries on the data present in the Elasticsearch cluster. It’s structured like an abstract syntax tree (AST) with two fundamental building blocks: leaf query clauses for pinpointing specific values within fields, and compound query clauses for orchestrating multiple queries using logical combinations or modifying their behavior. The context in which these clauses are used, either query or filter, significantly impacts their behavior. If we are to learn to write queries from scratch, we can investigate querying all the data in a particular index. For example, in MS SQL language, we say, Select * from employees, where employees is a table in the MS SQL database.

Here, in Console, we implement a similar logic to write a DSL query as follows:

GET kibana_sample_data_ecommerce/_search;

Here, kibana_sample_data_ecommerce is an index in Elasticsearch...