# The Atlas Search 'cene: Season 1

# The Atlas Search 'cene: Season 1

Welcome to the first season of a video series dedicated to Atlas Search!  This series of videos is designed to guide you through the journey from getting started and understanding the concepts, to advanced techniques.

## What is Atlas Search?

[Atlas Search][1] is an embedded full-text search in MongoDB Atlas that gives you a seamless, scalable experience for building relevance-based app features. Built on Apache Lucene, Atlas Search eliminates the need to run a separate search system alongside your database.

By integrating the database, search engine, and sync mechanism into a single, unified, and fully managed platform, Atlas Search is the fastest and easiest way to build relevance-based search capabilities directly into applications.

> Hip to the *'cene*
> 
> The name of this video series comes from a contraction of "Lucene",
> the search engine library leveraged by Atlas. Or it's a short form of "scene". 

## Episode Guide

### **[Episode 1: What is Atlas Search & Quick Start][2]**

In this first episode of the Atlas Search 'cene, learn what Atlas Search is, and get a quick start introduction to setting up Atlas Search on your data.  Within a few clicks, you can set up a powerful, full-text search index on your Atlas collection data, and leverage the fast, relevant results to your users queries.

### **[Episode 2: Configuration / Development Environment][3]**

In order to best leverage Atlas Search, configuring it for your querying needs leads to success. In this episode, learn how Atlas Search maps your documents to its index, and discover the configuration control you have.

### **[Episode 3: Indexing][4]**

While Atlas Search automatically indexes your collections content, it does demand attention to the indexing configuration details in order to match users queries appropriately. This episode covers how Atlas Search builds an inverted index, and the options one must consider.

### **[Episode 4: Searching][5]**

Atlas Search provides a rich set of query operators and relevancy controls. This episode covers the common query operators, their relevancy controls, and ends with coverage of the must-have Query Analytics feature.

### **[Episode 5:  Faceting][6]**

Facets produce additional context for search results, providing a list of subsets and counts within. This episode details the faceting options available in Atlas Search.

### **[Episode 6: Advanced Search Topics][7]**

In this episode, we go through some more advanced search topics including embedded documents, fuzzy search, autocomplete, highlighting, and geospatial.

### **[Episode 7:  Query Analytics][8]**

Are your users finding what they are looking for? Are your top queries returning the best results? This episode covers the important topic of query analytics. If you're using search, you need this!

### **[Episode 8:  Tips & Tricks][9]**

In this final episode of The Atlas Search 'cene Season 1, useful techniques to introspect query details and see the relevancy scoring computation details. Also shown is how to get facets and search results back in one API call.

  [1]: https://www.mongodb.com/atlas/search
  [2]: https://www.mongodb.com/developer/videos/what-is-atlas-search-quick-start/
  [3]: https://www.mongodb.com/developer/videos/atlas-search-configuration-development-environment/
  [4]: https://www.mongodb.com/developer/videos/mastering-indexing-for-perfect-query-matches/
  [5]: https://www.mongodb.com/developer/videos/query-operators-relevancy-controls-for-precision-searches/
  [6]: https://www.mongodb.com/developer/videos/faceting-mastery-unlock-the-full-potential-of-atlas-search-s-contextual-insights/
  [7]: https://www.mongodb.com/developer/videos/atlas-search-mastery-elevate-your-search-with-fuzzy-geospatial-highlighting-hacks/
  [8]: https://www.mongodb.com/developer/videos/atlas-search-query-analytics/
  [9]: https://www.mongodb.com/developer/videos/tips-and-tricks-the-atlas-search-cene-season-1-episode-8/