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Coursera

Kibana 8.x – A Quick Start Guide to Data Analysis

Packt via Coursera

Overview

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This course introduces learners to Kibana, focusing on its data exploration, visualization, and dashboard-building capabilities. With a structured approach, learners will be equipped to transform raw data into actionable insights using Kibana's powerful features. Practical examples and step-by-step guides ensure an intuitive understanding of Kibana’s interface. By the end, learners will be able to create and share interactive dashboards and use advanced analytics features to drive business decision-making. Designed for professionals, this course combines theoretical concepts with real-world applications. It equips learners to use Kibana for efficient data management and visualization, enhancing their analytics workflow. This hands-on guide allows learners to master Kibana through practical, expert-led lessons. Whether you're a data analyst or business user, this course will help you leverage Kibana for meaningful data analysis. This course is beneficial for data analysts, data engineers, and business users with a basic understanding of Elasticsearch. Knowledge of data analysis tools is recommended for the best experience.

Syllabus

  • Introduction to Kibana
    • In this section, we introduce Kibana as an open-source UI for Elasticsearch, covering setup, configuration, and data integration to enable effective data visualization and management within the Elastic Stack.
  • Creating Data Views and Introducing Spaces
    • In this section, we covers creating data views, configuring spaces, and managing saved objects in Kibana.
  • Discovering the Data through Discover
    • In this section, we explore Kibana Discover to analyze data, construct KQL queries, and save searches for efficient data retrieval and reuse.
  • How About We Visualize
    • In this section, we covers Kibana visualization tools like Lens, Canvas, and maps for interactive data displays.
  • Powering Visualizations with Near Real-Time Updates
    • In this section, we explore TSVB for real-time data visualization, focusing on annotations, aggregations, and customization to enhance time series analysis.
  • Data Analysis with Machine Learning
    • In this section, we explore anomaly detection in time series data, entity-centric analysis, and alert configuration using Kibana's machine learning tools for improved data insights and proactive issue resolution.
  • Graph Visualization
    • In this section, we explore graph visualization in Elasticsearch to uncover relationships between data points, focusing on creating, customizing, and troubleshooting graphs for applications like fraud detection and recommendations.
  • Finally, the Dashboard
    • In this section, we covers creating dashboards to visualize and analyze data effectively.
  • ES|QL and Advanced Kibana Concepts
    • In this section, we explore ES|QL fundamentals and advanced Kibana concepts to enhance data querying, visualization, and analysis efficiency through practical skills and structured workflows.
  • Query DSL and Management through Kibana
    • In this section, we explore Query DSL for precise data retrieval and complex query design, focusing on Boolean logic, RBAC, and watcher configurations to enhance data management and security.

Taught by

Packt - Course Instructors

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