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.

Dashboard Development: Building interactive dashboards to consolidate and present insights from various data sources.

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 jаvascript.

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

IntroductionThe 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 InterestsIn 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 ExplorationThis 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 TrackingMetric 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 BeyondThis 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.ConclusionIn conclusion, this course equips participants with a robust skill set in using Kibana and Elasticsearch for diverse data analysis needs. Through structured projects and hands-on exercises, learners have explored key functionalities such as data loading, visualization creation, dashboard compilation, and advanced querying techniques. They have gained practical insights into leveraging these tools to derive actionable insights from complex datasets, monitor system metrics in real-time, and enhance organizational decision-making processes. With a solid foundation in Kibana and Elasticsearch, graduates of this course are well-prepared to apply their knowledge in professional settings, driving innovation and efficiency through data-driven strategies.

Overview

Section 1: Project on Kibana - Analyzing Employee Browsing Interests

Lecture 1 Introduction to Project

Lecture 2 Load Data Elasticsearch

Lecture 3 Analysis of Data in Kibana

Lecture 4 Creation of Visualization

Lecture 5 Creation of Dashboard

Lecture 6 Conclusion

Section 2: Project on Kibana - Super Market Sales Analysis and Exploration

Lecture 7 Introduction to Project

Lecture 8 Data Upload Kibana

Lecture 9 Visualization

Lecture 10 Visualization Continue

Lecture 11 Dashboard

Lecture 12 Summary

Section 3: Project on Kibana - Metric Monitoring and Tracking

Lecture 13 Introduction to Project

Lecture 14 Project Setup Overview

Lecture 15 Metric beat Overview

Lecture 16 Visualize and Dashboard Creation

Lecture 17 Request Response

Lecture 18 Python Programming Part 1

Lecture 19 Python Programming Part 2

Lecture 20 Python Programming Part 3

Lecture 21 Python Programming Part 4

Section 4: Elasticsearch with Logstash and Kibana - Beginners to Beyond

Lecture 22 Introduction to Comprehensive Elastic Stack (Elk Stack) Training

Lecture 23 Introduction to Nosql

Lecture 24 Installation of Elastic Search

Lecture 25 Important Key Definitions

Lecture 26 Cluster of of Elastic Search

Lecture 27 Mappings

Lecture 28 Mappings Continues

Lecture 29 Types of Datatable Elastic Search

Lecture 30 IP Keyword Date and Nested

Lecture 31 Dev Tools

Lecture 32 Elasticsearch Analyzers

Lecture 33 Analyzers Consists of 3 Components

Lecture 34 Tokenized Inverted Index

Lecture 35 Token Filter

Lecture 36 Transactions

Lecture 37 Edge Gram and Synoym Analyzer

Lecture 38 Cluster Dot Name

Lecture 39 Discovery Configuration

Lecture 40 Gateway Configuration

Lecture 41 Field Data

Lecture 42 Split Brain

Lecture 43 How to Avoid the Split-Brain Problem

Lecture 44 Query Context

Lecture 45 Filter Context

Lecture 46 Match Phrase Query

Lecture 47 Text and Title Query

Lecture 48 Term Level Query

Lecture 49 Term Level Query Continue

Lecture 50 More on Term Level Query

Lecture 51 Range Query

Lecture 52 Range Query Continue

Lecture 53 Prefix Exists Query

Lecture 54 Geo Shape Data Shape

Lecture 55 Geo Shape Data Shape Example

Lecture 56 Geo Point Sort Query and its Example

Lecture 57 Geo Distance Query Filter and its Example

Lecture 58 Geo Polygon Query

Lecture 59 Geo Polygon Query Continues

Lecture 60 Working on Behaviour of Keywords

Lecture 61 Convert SQL Query to Elasticsearch Queries

Lecture 62 Convert SQL Query to Elasticsearch Queries Continues

Lecture 63 Working with Data Model

Lecture 64 More on Data Model

Lecture 65 Example of Data Model

Lecture 66 Example of Data Model Continues

Lecture 67 Working with Multiple Custom Analyzers

Lecture 68 Solution Multiple Custom Analyzers

Lecture 69 More on Multiple Custom Analyzers

Lecture 70 Dynamic Templates in Elastic Search Queries

Lecture 71 Example of Dynamic Templates

Lecture 72 Path and Pattern Dynamic Templates

Lecture 73 Example of Path and Pattern

Lecture 74 Working with Attributes Mapping in Dynamic Template

Lecture 75 Working with Attributes Mapping in Dynamic Template Continues

Lecture 76 Creating Mapped Attribute Area Object

Lecture 77 Cluster APIs in Elasticsearch Queries

Lecture 78 Example of Cluster APIs

Lecture 79 Cluster Reroutes

Lecture 80 Example of Cluster Reroutes

Lecture 81 Indices APIs in Elastic Search Queries

Lecture 82 Example of Creating a Slot Index

Lecture 83 Open and Index APIs

Lecture 84 Get and Put Mapped in Index APIs

Lecture 85 Working Indices Aliases using Index APIs

Lecture 86 Document APIs in Elastic Search Queries

Lecture 87 Working with Get APIs in Document APIs

Lecture 88 Working with Delete APIs in Document APIs

Lecture 89 Working with Update and Bulk APIs in Document APIs

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.