By the end of this course, learners will be able to apply nested queries, implement parent-child mappings, and execute relational-style joins in Elasticsearch for advanced data modeling. You will gain the skills to index event-driven data, use inner hits for detailed matches, and optimize query performance with global ordinals.

This course is designed to bridge the gap between traditional relational databases and Elasticsearch’s document-oriented model. Through practical workshops and structured lessons, learners will explore application-side joins, nested queries, and indexing best practices. The course then advances into modeling complex one-to-many relationships using parent-child queries, with hands-on exercises for has_child and has_parent functionalities. What makes this course unique is its step-by-step alignment of relational concepts with Elasticsearch capabilities, ensuring you not only understand the theory but also practice real-world applications. Whether you are a data engineer, developer, or search specialist, this course equips you with essential strategies to analyze, structure, and query large-scale datasets efficiently in Elasticsearch.