This Elasticsearch course is for those who want to learn how to use Elasticsearch technology to store and query large volumes of data with easy scalability. Whether you are building a full-text search engine for your clients or want to store, analyze, and visualize large volumes of logs and business data in one place, this course is designed for you.
Throughout the course, each participant will understand each concept and apply it immediately in practical labs. Also, the course materials provided allow for a refresher at any time.
- IT professionals who need to quickly store, search, and visualize large volumes of data efficiently
- Introduction to Elasticsearch and working with CRUD operations
- Mapping: index, types, fields, templates and dynamic properties
- Text analysis and search relevance for unstructured data
- Tokenization, filters, parsers, and language management
- Distributed queries, Query DSL and advanced filters
- Aggregations and summary calculation of data
- Suggestions and autocomplete for search interfaces
- Data modeling: relationships, subdocuments, parent-child links
- Stored queries and performance optimization mechanisms
- Basic knowledge of database systems
- Why Elasticsearch?
- Introduction
- CRUD operations and bulk indexing
- Mapping and basic settings
- Mapping
- Index structure and data types
- Dynamic properties and templates
- Introduction to text analysis
- Unstructured data and search relevance
- Text analysis
- Analyzers, tokenization and filters
- Language management and synonyms
- Data search
- Distributed search, Query DSL, advanced filters
- Aggregation
- Basic aggregations and recommended practices
- suggested
- Autocomplete and contextual suggestions
- Data modeling
- Relationships between objects and subdocuments
- Stored queries
- Percolator and other optimizations
There are no recommendations at this time.
