Udemy – Kibana and Elasticsearch: Data Analysis and Visualization 2024-6

Published on: 2024-08-15 14:15:41

Categories: 28

Description

Kibana and Elasticsearch: Data Analysis and Visualization course. This course provides a comprehensive journey to use these powerful tools in data analysis, visualization and system monitoring. Suitable for both beginners and those looking to further their knowledge, this course covers essential aspects from basic setup to advanced analysis techniques. Participants gain hands-on experience with real-world projects that simulate scenarios such as analyzing employee browsing behavior, optimizing supermarket sales, and real-time metrics monitoring. By the end of the course, students will have the skills to use Kibana and Elasticsearch to their full potential, and will be able to make informed decisions and apply actionable insights across multiple domains.

What you will learn:

Kibana and Elasticsearch Basics: Understanding the core functionality and architecture of Kibana and Elasticsearch.
Data loading and management: Techniques for loading and managing data in Elasticsearch, including indexing and mapping.
Creating visualizations: Building meaningful visualizations for effective data interpretation using Kibana.
Dashboard Development: Build interactive dashboards to consolidate and provide insights from various data sources.
Advanced Querying: Master advanced querying techniques in Elasticsearch for data retrieval and analysis.
Real-time data monitoring: Using Kibana for real-time data monitoring and alerting.
Elasticsearch Cluster Management: Managing Elasticsearch clusters for scalability and performance.
Python integration: Python integration for data preprocessing, analysis, and visualization within Kibana and Elasticsearch.
Benchmark Tracking: Setting up and configuring benchmark tracking and monitoring using Kibana.
Practical projects: applying the skills learned through practical projects such as analyzing the browsing behavior of employees, sales trends in supermarkets.

This course is suitable for people who:

Data analysts and data scientists: who want to enhance their skills in data visualization and analysis using Kibana and Elasticsearch.
Database administrators: who are looking to expand their knowledge of managing and querying data using Elasticsearch.
Developers: Interested in integrating Elasticsearch and Kibana into their applications for powerful data insights.
Business Intelligence Professionals: Looking to use Kibana’s visualization capabilities for reporting and analysis.
IT professionals: Interested in learning about scalable data warehousing and real-time analytics using Elasticsearch.
Students and researchers: Explore data visualization and analysis tools in academic or research environments.
Big data and analytics enthusiasts: who want to learn how to use Elasticsearch and Kibana to effectively manage and visualize large data sets.

Kibana and Elasticsearch: Data Analysis and Visualization course specifications

Publisher: Udemy
Lecturer: EDUCBA Bridging the Gap
Training level: beginner to advanced
Training duration: 13 hours and 4 minutes
Number of courses: 89

Course headings

Kibana and Elasticsearch: Data Analysis and Visualization

Kibana and Elasticsearch: Data Analysis and Visualization course prerequisites

Basic Understanding of Data Analysis: Familiarity with concepts related to data analysis and visualization.
Fundamental Knowledge of Databases: Understanding of database structures and querying (SQL knowledge is beneficial).
Basic Command Line Skills: Ability to navigate and execute commands in a command-line interface (CLI).
Basic Programming Skills: Familiarity with programming concepts, especially in languages like Python or JavaScript.
Knowledge of Web Technologies: Understanding of web technologies such as HTTP, JSON, and RESTful APIs.
System Requirements: Access to a computer with internet connectivity, capable of running Kibana and Elasticsearch.
Motivation and Learning Commitment: Willingness to engage in hands-on exercises and projects to apply learned concepts.