This is the code repository for Kibana 8.x – A Quick Start Guide to Data Analysis, published by Packt.
Learn about data exploration, visualization, and dashboard building with Kibana
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.
This book covers the following exciting features:
- Create visualizations using the Visualize interface in Kibana
- Build shareable search dashboards to drill down and perform advanced analysis and reporting
- Search data to make correlations and identify and explain trends
- Embed dashboards, share links, and export PNG, PDF, and CSV files and send them as attachments
- Configure and tweak advanced settings to best manage saved objects in Kibana
- Implement several types of aggregations working behind the scenes of extensive visualizations
If you feel this book is for you, get your copy today!
The code will look like the following:
GET kibana_sample_data_ecommerce/_search
{
"query": {
"match": {
"customer_first_name": "Eddie"
}
}
}
Following is what you need for this book: If you’re a data analyst or a data engineer, this book is for you. It’s also a useful resource to database administrators, analysts, and business users looking to build a foundation in creating intuitive dashboards using Kibana 8.x and data analysis techniques for improved decision making. Foundational knowledge of Elasticsearch fundamentals will provide an added advantage.
Krishna Shah is a Data Architect with over 9 years of experience in the field of Data engineering and Data Analytics. Being based out in Australia, she has been a part of the official Elasticsearch - Kibana Trainings & has been into creating the courseware for the same. Moreover, she had been an integral part of designing and maintaining data engineering pipelines & thereby using Kibana for the visualisation and analytics needs whilst she had worked in a startup based in India.