# Connector Features

Once the connection is established, the connector performs three key tasks:

* Crawling: Fetches metadata from the data source.
* Profiling: Analyzes the data to generate statistics and quality metrics.
* Lineage Building: Maps the data flow and transformations across systems.

Below is an example of crawling and profiling.

<figure><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXdtsvpd5LqwjJ6OzdsTXQ7qJS4IvmzYsUDn1KMVMEkC8YWkvn1-D8qiUhcRYhZ05zvnGzhoRLz3mXt4MLbN0WC364uWrWGCBox-vDKOdcaS6xZyuL47y2ovDrH9ZVhtJPBINr8m?key=kU5fqtI4eAzquyCyuBsp-g" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
Crawling, Profiling, and Lineage building vary depending on the connector type.
{% endhint %}

### Connection, Crawling, Profiling & Lineage Workflow

1. **Set Up Connection**
   1. Users connect to the source system using supported protocols such as JDBC or REST APIs. The system establishes a connection to the data source.
2. **Metadata Crawl**
   1. The system fetches metadata from the connected source. It collects information such as tables, columns, reports, and file structures.
   2. Fetched metadata appears in the data catalog.
3. **Data Profiling (If Applicable)**
   1. The system builds statistics for data objects.
   2. Profiled data appears in the data catalog to support analysis.
4. **Build Lineage (If Applicable)**
   1. The system builds lineage to show the flow of data across systems.
   2. Lineage helps users trace the origin of data, understand transformations, and analyze downstream impact.

<figure><img src="https://1813356899-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FhTnkoJQml0pok9awFDhx%2Fuploads%2FVZgjsoNrclGiIhwYmDdd%2Fimage.png?alt=media&#x26;token=c0cfb835-6c87-4fb3-97bb-6360057d9553" alt=""><figcaption></figcaption></figure>

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