Data Analysis with Kibana - Virtual
Instructor-led Virtual Training
|Location||Apr 2020||May 2020||Jun 2020||Jul 2020||Aug 2020|
|US Central Time||
May 4 – May 7||
Jun 8 – Jun 11|
|US Pacific Time||
May 26 – May 29||
Jun 22 – Jun 25|
|Central European Summer Time - English||
May 25 – May 28||
Jun 29 – Jul 2|
|Singapore (SGT) Time - English||
Jun 29 – Jul 1|
|Australian Eastern Standard Time - English||
Jun 29 – Jul 1|
Classes in bold are guaranteed to run!
A powerful search and analytics engine needs an equally powerful user interface for creating advanced visualization and performing deeper analysis. This course focuses on exactly that, using Kibana to analyze data in Elasticsearch.
Starting with the fundamentals, you will learn the core concepts of data analysis using Kibana — from simple aggregation-based charts to complex geo based visualization to complex time series visualizations — through lectures, labs, and Q&A sessions. You will also learn how to create visualizations and dashboards across a variety of data sets, as well as how to manage Kibana by handling saved objects and creating spaces. By the end of this course, you will be able to easily find answers and anomalies in your Elasticsearch data sets using Kibana. After completing this course, you will be prepared for the Elastic Certified Analyst exam.Topics Covered
- Kibana fundamentals
- Kibana searches
- Kibana visualizations
- Kibana visual builder
- Kibana geo visualizations
- Kibana dashboards
- Kibana advanced tools for analysts
- Machine learning fundamentals
- Kibana interfaces
Any technical or non-technical users, including Data Analysts, Security Analysts, Operations Analysts, DevOps, and other business professionals
- Laptop with Wi-Fi connectivity
- Mac, Linux, or Windows
- Latest version of Chrome or Firefox (other browsers not supported)
- Disable any ad blockers and restart your browser before class
- Ensure that any VPNs on your laptop are disabled before class
Virtual Classroom Information
Virtual classroom trainings are delivered in four, six or eight-hour sessions of live lectures and lab time, with scheduled breaks throughout the session.
Open a specific offering (listed at the top of the page) to see the hours in which it will be held.
We encourage participants to set up their systems prior to logging into the training environment the first day of the class and logged in 15 minutes prior to the start of class each day.