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Elasticsearch mappings turn logs from unstructured text into usable data. In this video, we explain what mappings are, how they define fields like text, number, and date, and why they matter. With the right mappings, Elasticsearch can filter error codes, sort by response time, and group results by browser, region, or version.

Ever wondered how Elasticsearch can search any kind of data? In this video, we break it down with a simple deck of cards analogy that makes indexing easy to understand. Each card is like a JSON document with fields and values, suit, color, number, type. Combine them and you’ve built an index, giving Elasticsearch the power to answer queries like “show me all the red cards” or “show me only the face cards.” If you can describe it, you can index it, and if you can index it, you can search it.

Ever wondered how Elasticsearch actually works? In this quick breakdown, I’ll use a simple spreadsheet analogy to explain the basics from documents and indices to shards, CRUD operations, and mappings. You’ll see how Elasticsearch stores data as JSON documents, splits indices into shards for scalability, uses CRUD with ID hashing for fast lookups, and applies mappings to organize text, numbers, and labels.

What is vector search? In this breakdown, learn how vector search leverages machine learning to capture the meaning and context of unstructured data by transforming it into a numeric representation that is stored in a vector database. This video also explains the difference between sparse and dense embeddings, and how vector search differs from semantic search and lexical search.

Ever wondered how Wikipedia loads answers instantly? Or how does your Uber update in real-time? That’s Elastic Search working behind the scenes. In this video, I break down how Elastic powers lightning-fast, scalable search for complex data from ride requests to stock prices.

What is semantic intent, and why is it crucial in the age of *AI search?* In this episode of Quick Question, we break down how semantic *intent interprets* the meaning behind your query in semantic search. About Elastic Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.

In this video, I’ll explain what semantic search is and how it’s different from traditional keyword search. I’ll walk you through the limitations of lexical search, what we mean by semantic intent, and how vector search plays a role under the hood. About Elastic Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500.

Get ready to say 'Hasta la vista, baby' to outdated search methods as we take a closer look at semantic search, using a data set of some all-time favorite sci-fi and horror movies! Join Ugo Sangiorgi, principal product marketing engineer, for a 20-minute coding session to learn about: Key Highlights: Resources: If you’re looking to add AI-driven search to your app, product, or website, this session is for you. Engage with us in the chat, share your thoughts, and feel free to ask questions. Let's dive into the world of hybrid search with Elasticsearch!