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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Successfully delivered 9 sessions for over 10 professionals

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1,150

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Course Fee 1,150
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1,150 (USD)
  • Live Training (Duration : 24 Hours)
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  • Live Training (Duration : 24 Hours)
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  • Classroom Training fee on request

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You can request classroom training in any city on any date by Requesting More Information

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Course Advisor

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Sunny Sirohi

6+ Years Experience

Highly motivated corporate trainer with 5+ years of experience in delivering training in Linux for Red Hat and other vendors like SUSE, LPI, and LF across diverse industries. Proven success in leveraging educational theories and methodologies to design, develop, and deliver successful training and integrate instructional technologies. Adapt at organizing and facilitating management in Team Building, Imparting Technical Training, Consulting, and Management.

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.

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