# Beacon : Basics

Beacons are a **powerful Gen AI-driven feature** that enable the extraction of insights from **unstructured data**, such as **reviews, call transcripts, emails, and customer feedback**. By **processing text-based content**, Beacons **generate structured insights** that can be seamlessly integrated into traditional analytics workflows.

#### **Beacon Availability**

⚡ **Beacons currently work only for**:

* **Cached Data Sources**
* **Uploaded Files**

🚨 **Beacons are an Enterprise Feature**

* This feature is **not available for all users** and is exclusive to enterprise-tier customers.

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### **Understanding the Basics of Beacons**

#### **1. Beacons Are Linked to Data Tables**

Each **Beacon is connected to a specific data table**, meaning it extracts insights directly from a designated dataset. For example, in the **Disneyland reviews dataset**, the Beacon is linked to the **reviews table**, processing the unstructured comments into meaningful insights.

#### **2. Beacons Contain Nodes**

* A **Node** is an **individual insight or fact** extracted from your data.
* Each Beacon can have **multiple nodes**, allowing for **different types of insights**.
* **Example Nodes in Disneyland Reviews**:
  * **Sentiment** (Positive, Neutral, Negative)
  * **Complaints** (Food, Rides, Wait Times, Staff)
  * **Emotion** (Anger, Joy, Frustration, Excitement)

#### **3. Beacons Become Usable as Structured Data**

* Once a **Beacon is processed**, it **creates a new structured table**.
* This **new table can be joined or combined** with other tables for **deeper analytics**.
* For example, the **Disneyland review insights** table can be **merged with CRM data** to analyze customer satisfaction trends over time.


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