Elastic: Getting started with Elasticsearch

Whether you're building a search feature, analyzing data, or exploring AI-powered retrieval, Elasticsearch Serverless gives you a single, scalable platform to do it all without managing infrastructure.

In this beginner-friendly webinar, we'll move beyond isolated API calls and instead build a real mental model of how Elasticsearch works. Using a hands-on dataset containing text, structured fields, geo coordinates, and vector embeddings, we'll progressively layer concepts from the ground up, so you understand not just what to do, but why you're doing it.

By the end of this session, you'll walk away with a clear foundation in Elasticsearch core concepts, from schema design and full-text search all the way to semantic retrieval and AI-powered workflows.

Highlights

• Schema design: Define explicit mappings for text, keywords, geo, and vector fields, and learn why structure matters from the start.
• Lexical search and relevance: Explore match, multi_match, and bool queries, and understand how BM25 scoring and the inverted index power ranked search.
• Aggregations and geospatial search: Summarize your data and run location-aware queries, all within the same engine.
• Semantic and hybrid search: Combine lexical and vector-based retrieval and explore reciprocal rank fusion (RRF) ranking, semantic_text, and the retrieval augmented generation (RAG) pattern for AI-powered workflows.
• ES|QL: Query your data with a readable, pipe-based syntax that's great for exploration and iterative analysis.