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Data Analysis with Kibana Course Overview

Data Analysis with Kibana Course Overview

The Data Analysis with Kibana course provides comprehensive training on leveraging Kibana for insightful data exploration and visualization. It's designed to help learners understand their data through the Elastic Stack effectively. Module 1 lays the foundation by introducing Kibana's capabilities, including data exploration with the Discover interface and creating visualizations with Lens. As learners progress through the course, Modules 2 through 9 delve deeper into specific functionalities like Kibana search optimization, crafting sophisticated visualizations, and utilizing the visual builder for time series data. The course also covers geo visualizations, dashboard creation, advanced tools for analysts, and the fundamentals of machine learning to analyze large, unused datasets. Additionally, learners will explore various Kibana interfaces and applications, gaining skills to generate reports, manage saved objects, and organize workspaces with Spaces. This course empowers learners to find answers in their data, build powerful dashboards, and apply advanced analysis techniques to uncover valuable insights, preparing them for real-world data challenges.

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  • Live Online Training (Duration : 24 Hours)
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  • Guaranteed-to-Run (GTR)
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♱ Excluding VAT/GST

Classroom Training price is on request

  • Live Online Training (Duration : 24 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

  • Can't Attend Live Online Classes? Choose Flexi - a self paced learning option
  • 6 Months Access to Videos
  • Access via Laptop, Tab, Mobile, and Smart TV
  • Certificate of Completion
  • Hands-on labs

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Course Prerequisites

To ensure a successful learning experience in our Data Analysis with Kibana course, the following minimum prerequisites are recommended for potential learners:


  • Basic understanding of data storage and retrieval concepts.
  • Familiarity with JSON and the structure of JSON data.
  • Knowledge of how to navigate and operate a web interface.
  • Experience with any programming or scripting language is beneficial but not mandatory.
  • Familiarity with basic concepts of databases and data querying.
  • An understanding of the fundamentals of Elasticsearch is advantageous as Kibana is part of the Elastic Stack.

By meeting these prerequisites, you will be well-prepared to dive into the course material and gain the most from your Data Analysis with Kibana training.


Target Audience for Data Analysis with Kibana

The Data Analysis with Kibana course by Koenig Solutions is designed for professionals looking to leverage data visualization and analysis using Elastic Stack.


Target Audience and Job Roles:


  • Data Analysts
  • Business Intelligence Professionals
  • IT Professionals working with large datasets
  • Elastic Stack (ELK) Users
  • Data Scientists interested in visualization
  • Security Analysts focusing on data monitoring
  • DevOps Engineers integrating monitoring solutions
  • Database Administrators seeking advanced data visualization tools
  • SEO Specialists and Web Analysts using data for optimization
  • Network Administrators utilizing data for network performance
  • Product Managers analyzing user data for product improvements
  • Marketing Analysts studying customer behavior and market trends
  • Software Developers who need to visualize application data
  • Data Journalists requiring visual storytelling techniques


Learning Objectives - What you will Learn in this Data Analysis with Kibana?

Introduction to Course Learning Outcomes:

Gain proficiency in data analysis using Kibana, mastering skills from visual exploration to advanced analytics and machine learning integration for comprehensive insights.

Learning Objectives and Outcomes:

  • Understand the core functions of Kibana within the Elastic Stack for data interpretation and analysis.
  • Navigate and utilize the Discover interface to explore datasets effectively.
  • Perform targeted data searches using the Kibana query bar and optimize search results with filters.
  • Create intuitive and customized visualizations using Kibana’s visualization tools, including Lens.
  • Build complex time series visualizations with Time Series Visual Builder (TSVB) for detailed temporal data analysis.
  • Develop and implement geographical data visualizations to represent density, movement, or positioning.
  • Construct and personalize Kibana dashboards to present data-driven insights to various audiences.
  • Utilize Kibana’s advanced analytical tools to create sophisticated visualizations, such as derivatives and moving averages.
  • Implement machine learning jobs within Kibana to analyze large datasets in an unsupervised manner.
  • Explore Kibana’s specialized interfaces, manage reporting, and organize workspaces with Spaces for better data management.