Kibana and Elasticsearch: Data Analysis and Visualization
Год выпуска: 2024
Производитель: Udemy
Сайт производителя:
https://www.udemy.com/course/kibana-and-elasticsearch-data-analysis-and-visualization/
Автор: EDUCBA Bridging the Gap
Продолжительность: ~13h4m
Тип раздаваемого материала: Видеоурок
Язык: Английский
Описание: Introduction
The course on Kibana and Elasticsearch offers a comprehensive journey into leveraging these powerful tools for data analysis, visualization, and system monitoring. Designed for both beginners and those looking to deepen their knowledge, this course covers essential aspects from basic setup to advanced analytics techniques. Participants will gain hands-on experience with real-world projects that simulate scenarios ranging from employee browsing behavior analysis to supermarket sales optimization and real-time metric monitoring. By the end of the course, students will have acquired the skills necessary to harness the full potential of Kibana and Elasticsearch, making informed decisions and driving actionable insights across various domains.
Section 1: Project on Kibana - Analyzing Employee Browsing Interests
In this section, students delve into the comprehensive analysis of employee browsing behaviors using Kibana. The project aims to uncover insights that can enhance organizational security and productivity by examining patterns and trends in browsing activities. Through loading data into Elasticsearch, analyzing it in Kibana, and creating intuitive visualizations and dashboards, participants gain practical skills in data exploration and presentation. By the conclusion of this section, learners will have a solid foundation in leveraging Kibana's capabilities for insightful data analysis and visualization.
Section 2: Project on Kibana - Super Market Sales Analysis and Exploration
This section focuses on leveraging Kibana for in-depth analysis of supermarket sales data. Participants will learn to upload and structure data in Kibana, create meaningful visualizations, and compile them into actionable dashboards. The project aims to extract actionable insights from sales data to optimize business operations and enhance decision-making processes. By the end of this section, students will have gained proficiency in using Kibana to analyze complex datasets and derive strategic insights for business improvement.
Section 3: Project on Kibana - Metric Monitoring and Tracking
Metric monitoring and tracking are vital for real-time insights into system performance and health. This section introduces participants to setting up Metricbeat for data collection, visualizing metrics, and creating dynamic dashboards in Kibana. The projects within this section aim to equip learners with the skills to monitor key metrics effectively, set up alerts for proactive management, and utilize Python for advanced data analysis and automation. By the conclusion of this section, students will be adept at using Kibana as a powerful tool for real-time metric monitoring and performance optimization.
Section 4: Elasticsearch with Logstash and Kibana - Beginners to Beyond
This comprehensive section provides a deep dive into the Elasticsearch, Logstash, and Kibana (ELK) stack, essential for managing and analyzing large-scale datasets. Participants will learn the fundamentals of installing and configuring Elasticsearch, mapping data structures, and using advanced querying techniques. The section also covers practical aspects such as cluster management, data modeling, and the use of custom analyzers for tailored search experiences. By mastering these tools and techniques, learners will be prepared to tackle complex data challenges and optimize data-driven decision-making processes effectively.
Содержание
07:23
07:36
Analysis of Data in Kibana
07:49
Creation of Visualization
08:15
Creation of Dashboard
07:37
Conclusion
01:21
03:36
Data Upload Kibana
06:26
Visualization
08:45
Visualization Continue
11:16
Dashboard
09:09
Summary
00:46
06:07
Project Setup Overview
05:55
Metric beat Overview
11:08
Visualize and Dashboard Creation
10:35
Request Response
07:40
Python Programming Part 1
07:14
Python Programming Part 2
07:37
Python Programming Part 3
08:37
Python Programming Part 4
07:21
Introduction to Comprehensive Elastic Stack (Elk Stack) Training
10:50
08:11
Installation of Elastic Search
09:11
Important Key Definitions
09:09
Cluster of of Elastic Search
07:10
Mappings
07:00
Mappings Continues
05:49
Types of Datatable Elastic Search
10:41
IP Keyword Date and Nested
08:21
Dev Tools
07:34
Elasticsearch Analyzers
11:01
Analyzers Consists of 3 Components
11:54
Tokenized Inverted Index
06:44
Token Filter
06:39
Transactions
11:48
Edge Gram and Synoym Analyzer
09:52
Cluster Dot Name
11:10
Discovery Configuration
06:33
Gateway Configuration
08:37
Field Data
07:07
Split Brain
08:45
How to Avoid the Split-Brain Problem
11:43
Query Context
09:20
Filter Context
07:52
Match Phrase Query
11:12
Text and Title Query
10:06
Term Level Query
07:51
Term Level Query Continue
07:24
More on Term Level Query
09:29
Range Query
08:30
Range Query Continue
08:22
Prefix Exists Query
10:58
Geo Shape Data Shape
12:02
Geo Shape Data Shape Example
04:46
Geo Point Sort Query and its Example
07:37
Geo Distance Query Filter and its Example
05:36
Geo Polygon Query
06:07
Geo Polygon Query Continues
08:00
Working on Behaviour of Keywords
11:35
Convert SQL Query to Elasticsearch Queries
11:18
Convert SQL Query to Elasticsearch Queries Continues
08:02
Working with Data Model
09:12
More on Data Model
10:53
Example of Data Model
10:28
Example of Data Model Continues
07:49
Working with Multiple Custom Analyzers
08:13
Solution Multiple Custom Analyzers
07:09
More on Multiple Custom Analyzers
07:14
Dynamic Templates in Elastic Search Queries
09:07
Example of Dynamic Templates
10:41
Path and Pattern Dynamic Templates
11:13
Example of Path and Pattern
04:32
Working with Attributes Mapping in Dynamic Template
11:51
Working with Attributes Mapping in Dynamic Template Continues
09:22
Creating Mapped Attribute Area Object
09:58
Cluster APIs in Elasticsearch Queries
12:36
Example of Cluster APIs
11:22
Cluster Reroutes
09:32
Example of Cluster Reroutes
12:22
Indices APIs in Elastic Search Queries
11:34
Example of Creating a Slot Index
11:30
Open and Index APIs
10:14
Get and Put Mapped in Index APIs
11:21
Working Indices Aliases using Index APIs
09:55
Document APIs in Elastic Search Queries
11:01
Working with Get APIs in Document APIs
08:09
Working with Delete APIs in Document APIs
11:19
Working with Update and Bulk APIs in Document APIs
11:49
Файлы примеров: не предусмотрены
Формат видео: MP4
Видео: AVC, 1280x720, 16:9, 30fps, ~1000kbps
Аудио: AAC, 44.1kHz, 128kbps, stereo