Data Analysis with Kibana Training Course

Highlights

Learn the fundamentals of data analysis with Kibana.
Query and filter your data with Elasticsearch powerful query languages.
Create impactful visualisations and interactive dashboards.
Explore advance features like machine learning, alerting and more.
Share your dashboards and reports

Course Details

Introduction:

Presentation of the Elastic Stack

Elasticsearch
Logstash
Beat Agents
Kibana
Important notions
Nodes
Shards
Indices
Datastreams
Mappings
Documents

The Discover Tab

o Discover Tab Usage
o The Date & Timepicker
o The Center Main Table
o Filtering and Searching Data
o Language Based Search queries (KQL, Lucene & ES|QL)
o Saving and Sharing Searches

Elasticsearch Aggregation Families

o Metric Aggregations
o Bucket Aggregations
o Pipeline Aggregations

Visualizations in Kibana

o Vega
o Maps
o Graphs
o Legacy Visualisations
o Key Principles of Data Visualization

Dashboards

o Dashboards Features and Settings
o Dashboard Controls

Advanced Usages

o Transform indices
o Adding Fields to documents with Runtime Fields
o Anomaly Detection & Machine Learning
o Alerting and Reporting with Kibana

Labs Throughout the Session:

o Lab 1 - Discover Tab (1)
o Lab 2 - Discover Tab (2) – Query Languages
o Lab 3 - Visualizations (1) - Lens
o Lab 4 - Visualizations (2) – TSVB, Maps & Graph
o Lab 5 - Dashboards
o Lab 6 - Transform Indices

Who should attend

Data Analysts / Scientists
Statisticians
Business Analysts
DevOps / SecOp

Feedback

4.8 out of 5 average

"Good introduction to Apache Spark. The trainer was great at talking us through the information, specifically optimisation methods. He spoke slowly and concisely which really got his points across. He effectively tailored the course to our specifications which we also appreciated."

RL, Financial Crime Technologist, Apache Spark, April 2021

“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and the Instructor handled this particularly well - very impressive”

Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022

Certification

Every delegate will be entitled to a certificate of achievement on completion of the course.

If you are missing your certificate - please use the link below to apply - you can also use this link to sign up for the JBI Training newsletter to receive technology tips directly from our instructors - Analytics, AI, ML, DevOps, Web, Backend and Security.

More about this course

A powerful search and analytics engine needs an equally powerful user interface for creating advanced visualizations and performing deeper analysis. This course focuses on exactly that, using Kibana to analyze data in Elastic. Starting with the fundamentals, you will learn the core concepts of
data analysis using Kibana — from simple aggregation-based charts to complex geo-based visualizations to results of machine learning jobs of complex time series data — through lectures, labs, and Q&A sessions. You will also learn how to create visualizations and interactive 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

FAQs

JBI Training offers two courses in this group. Elasticsearch Engineer is a four-day comprehensive programme covering the full Elasticsearch stack for engineers who need to deploy, manage, and query Elasticsearch in production. Data Analysis with Kibana is a two-day course focused on using Kibana — Elasticsearch's visualisation and analytics layer — for data exploration, dashboard creation, and operational monitoring. Both courses are available as scheduled classroom sessions in London, as live online instructor-led training, or as customised onsite programmes for engineering and data teams.

Elasticsearch is an open-source, distributed search and analytics engine built on Apache Lucene and developed by Elastic. It is designed to store, search, and analyse large volumes of data in near real-time. It is widely used for full-text search across applications and websites, log and event data analysis, security information and event management (SIEM), application performance monitoring, e-commerce product search, and operational intelligence dashboards. Elasticsearch is the core component of the Elastic Stack (also known as the ELK Stack), which combines Elasticsearch with Logstash (data ingestion), Kibana (visualisation), and Beats (lightweight data shippers).

The four-day Elasticsearch Engineer course provides comprehensive coverage of Elasticsearch for engineers responsible for deploying, administering, and querying Elasticsearch in real environments. Topics include the Elasticsearch architecture and cluster model, indexing and mapping data, the Elasticsearch Query DSL for search and aggregation, data ingestion using Logstash and Beats, cluster management and administration, performance tuning and optimisation, security configuration, snapshot and restore for backup, and scaling Elasticsearch for production workloads. The course includes hands-on labs throughout and is suited to DevOps engineers, backend developers, data engineers, and infrastructure professionals who work with or are adopting Elasticsearch.

The two-day Data Analysis with Kibana course focuses on using Kibana — the visualisation and analytics front-end for the Elastic Stack — to explore, analyse, and present data stored in Elasticsearch. Topics covered include the Kibana interface and Discover tool for data exploration, creating visualisations including bar charts, line charts, maps, and metric panels, building and sharing interactive dashboards, using Kibana Lens for intuitive drag-and-drop analytics, working with time-series data, Canvas for pixel-perfect visual reporting, and an introduction to Kibana's machine learning and alerting features. It is suited to data analysts, operations teams, and DevOps professionals who need to derive insights and build monitoring dashboards from Elasticsearch data.

Traditional relational databases such as MySQL, PostgreSQL, and SQL Server store structured data in tables with defined schemas and are optimised for transactional workloads — inserting, updating, and retrieving records with precise queries. Elasticsearch is a document store optimised for full-text search, unstructured or semi-structured data, and analytical queries across very large datasets in near real-time. It excels at searching across free-text fields, handling variable data structures, and aggregating across millions of documents quickly. Many organisations use both — a relational database for transactional data and Elasticsearch as a search and analytics layer on top of that data, often populated via a data pipeline using Logstash or Beats.

Yes. Both courses can be delivered as customised onsite or online programmes for corporate engineering and data teams. Content and lab exercises can be tailored to the team's existing Elastic Stack version, deployment environment — whether on-premises, on Elastic Cloud, or hosted on AWS, Azure, or Google Cloud — and specific use cases such as log analytics, security monitoring, application search, or operational dashboards. JBI has delivered Elasticsearch and DevOps-related training for engineering teams at organisations including the BBC, NHS, RBS, Sky, EDF, and Cisco.

Yes. The Elastic Stack is updated regularly with new features across Elasticsearch, Kibana, Logstash, and Beats, and JBI's training content is continuously reviewed to reflect the latest stable release. This includes updates to Kibana Lens and the Kibana interface, new Elasticsearch query and aggregation capabilities, developments in Elastic's AI and machine learning features — including semantic search and vector search capabilities that are increasingly central to modern Elasticsearch deployments — and changes to Elastic's cloud and licensing model. Delegates learn skills that are current and applicable to the version of the Elastic Stack in use in their organisation today.

Learn to create impactful visualisations & interactive dashboards with Kibana & the underlying strength of Elasticsearch.

Public Courses

Customised Courses

Highlights

Course Details

Introduction:

Who should attend

Feedback

4.8 out of 5 average

Certification

More about this course

FAQs

Highlights

Course Details

Introduction:

Who should attend

Feedback

4.8 out of 5 average

Certification

More about this course

FAQs

What Elasticsearch and Kibana training courses does JBI Training offer?

What is Elasticsearch and what is it used for in professional environments?

What does the Elasticsearch Engineer course cover?

What does the Data Analysis with Kibana course cover?

What is the difference between Elasticsearch and traditional relational databases?

Can Elasticsearch and Kibana training be customised for a corporate team?

Are Elasticsearch and Kibana courses kept up to date with the latest Elastic Stack releases?

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