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Introduction to ELK Stack
An overview of ELK Stack
Why choose ELK?
Architecture of ELK
An explanation of Elastic Search Logstash and Kibana
Introduction to Logstash
A brief explanation of Logstash
Installation process
Log file configuration
Stashing process of the first event
Analyzing logs with Logstash
Uses of input and output
Execution model
Introduction to Elastic Search
An overview of Elastic Search
Installation and running process
Indexing documents list
Saving the documents
Searching the documents
Searching in Depth
Organized Search
Full-text Search
Intricate Search
Phrase Search
Underlining the Search
Multi-field Search
Proximity Matching
Partial Matching
Dealing with Human Languages
An introduction to various human languages
Identifying Words
Controlling Tokens
Decreasing Words to their actual Root Form
Stop words: Performance versus Precision
Typographical Errors and Spelling Mistakes
An insight into concepts
A brief introduction to Aggregation
Analysis process
Filtering Process of the Aggregations and Queries
Sorting Multivalue Loads
Expected Aggregation
Doc Values and Field Data
Introduction to Data Modeling
Elastic Search versus RDBMS
Relationships handling
Nested objects
Scale Designing
Major Geo Points
Geo Hashes
Geo Aggregations
Geo Shapes
Introduction to Kibana
An overview of Kibana
Installation process of Kibana
Sample data loading process
Discovering the saved data
Visualization of the data
Working with the Dashboard
Discovering the Data in Depth and Dashboard Analysis
Set-up of Time Filter
Searching of the saved data
Filtering by the Field
Viewing the document data
Viewing the document context
Viewing the field statistics
Data visualization
Dashboard analysis
Exploring the live data with the ELK Stack

To master the ELK Stack concepts, a candidate must-have the basic understanding of the following: SQL JSON Data Format Restful API