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This course explores Elasticsearch, an open-source, Java-based, full-text search and analytics engine that harnesses the power of the Lucene library. You’ll discover its capabilities as a versatile search engine for business data, offering the ability to store information, conduct searches on accurate and typo-ridden text, and perform real-time data analysis on vast datasets.

Throughout this course, you will gain comprehensive insights into the architecture of Elasticsearch and master the art of indexing and storing data within the Elasticsearch framework. You will progress to learn how to execute various types of queries, including fuzzy queries, and explore the intricacies of each operation and how it is implemented within Elasticsearch.

After completing the course, you’ll have gained a comprehensive understanding of the internal mechanisms of Elasticsearch and developed the skills to effectively use it for your data management and analysis requirements.

Elasticsearch Fundamentals: Indexing and Querying Data

# Overview

In ElasticSearch, **mapping** is the process of defining how a document and its fields are indexed and stored. It's similar to a table description in a relational database or a schema definition in a document store database (NoSQL). Mapping can be defined using the following:
 - Dynamic mapping
- Explicit mapping

Learn about the process of mapping and its types in Elasticsearch.

Introduction to Elasticsearch

Getting started on Elasticsearch

Text Analysis

Search on ElasticSearch

Aggregation

Conclusion

Mapping

Overview