Kibana and Elasticsearch: Data Analysis and Visualization

Kibana and Elasticsearch: Data Analysis and Visualization
Last updated 6/2024
Duration: 13h5m | .MP4 1280×720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.88 GB

Unlock the power of data with Kibana and Elasticsearch, mastering analytics and visualization for impactful insights.

What you’ll learn
Fundamentals of Kibana and Elasticsearch: Understanding the core functionalities and architecture of Kibana and Elasticsearch.
Data Loading and Management: Techniques to load and manage data in Elasticsearch, including indexing and mapping.
Visualization Creation: Creating meaningful visualizations to interpret data effectively using Kibana.
Advanced Querying: Mastering 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.
Integration with Python: Integrating Python for data preprocessing, analysis, and visualization within Kibana and Elasticsearch.
Metric Tracking: Setting up and configuring metric tracking and monitoring using Kibana.
Practical Projects: Applying learned skills through hands-on projects such as analyzing employee browsing behavior, sales trends in supermarkets

Requirements
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.

Description
Introduction
Section 1: Project on Kibana – Analyzing Employee Browsing Interests
Section 2: Project on Kibana – Super Market Sales Analysis and Exploration
Section 3: Project on Kibana – Metric Monitoring and Tracking
Section 4: Elasticsearch with Logstash and Kibana – Beginners to Beyond
Conclusion
Who this course is for:
Data Analysts and Data Scientists: Who want to enhance their skills in data visualization and analysis using Kibana and Elasticsearch.
Database Administrators: 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: Seeking to leverage Kibana’s visualization capabilities for reporting and analytics.
IT Professionals: Interested in learning about scalable data storage and real-time analytics using Elasticsearch.
Students and Researchers: Exploring tools for data analysis and visualization in academic or research settings.
Anyone Interested in Big Data and Analytics: Wanting to understand how to use Elasticsearch and Kibana for managing and visualizing large datasets effectively.

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