> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pylar.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

> Introduction to data views in Pylar - understand how views provide secure, governed access to your data

## What Are Data Views?

Data views in Pylar are SQL queries that define exactly what data AI agents can access. Think of views as a **window** into your data—agents can only see and query through these windows, never gaining direct access to your raw database tables.

```mermaid theme={null}
graph LR
    DS[Data Sources<br/>Snowflake, BigQuery, etc.]
    VIEW[SQL View<br/>Governed Query]
    AGENT[AI Agent]
    
    DS -->|Raw Data| VIEW
    VIEW -->|Scoped Data| AGENT
    
    style VIEW fill:#FF4017,stroke:#CC3300,color:#fff
```

## Views vs Raw Database Access

### The Problem with Direct Access

Giving AI agents direct database access means:

* ❌ Agents can query any table or column
* ❌ No control over what data is exposed
* ❌ Security risks from accidental or malicious queries
* ❌ Difficult to audit and monitor access
* ❌ Compliance challenges

### The Pylar Solution: Views

With Pylar views:

* ✅ **Complete Isolation**: Agents only access data through your defined views
* ✅ **Fine-Grained Control**: You decide exactly what data is available
* ✅ **Security by Design**: Views are the only access level—no exceptions
* ✅ **Full Audit Trail**: Every query goes through your views and is logged
* ✅ **Compliance Ready**: Easy to demonstrate data governance

<Warning>
  Views are the **only** access level AI agents get. They never have direct database access, ensuring complete security and governance.
</Warning>

## How Views Work in Pylar

### The View Lifecycle

1. **Create**: Write SQL queries in Pylar's SQL IDE
2. **Test**: Run queries to verify results
3. **Save**: Save queries as views in your project
4. **Build Tools**: Create MCP tools on top of views
5. **Publish**: Make tools available to AI agents
6. **Monitor**: Use Evals to see how agents interact with views

### View Organization

Views are organized within **projects**:

* Each project contains multiple views
* Views can reference different data sources
* You can create views that join across multiple databases
* Projects help organize views by use case or team

<Info>
  Projects provide a logical way to group related views and tools together. For example, you might have a "Customer Analytics" project with multiple views for different analysis needs.
</Info>

## Key Concepts

### Views Are Queries

A view is essentially a saved SQL query:

* Write standard SQL queries
* Use any SQL features your database supports
* Join tables, filter data, aggregate results
* Cross-database joins are supported

### Views Are Secure

* Agents can only query through views
* You control what columns and rows are accessible
* Sensitive data can be excluded or masked
* Row-level security can be implemented

### Views Are Flexible

* Multiple MCP tools can be created on a single view
* Each tool can have different parameters or purposes
* Views can be updated anytime
* Changes reflect automatically in all connected agents

## Benefits of Using Views

### For Security Teams

* **Complete Control**: Define exactly what data agents can access
* **No Raw Access**: Eliminate the risk of direct database queries
* **Audit Trail**: Every query is logged and traceable
* **Compliance**: Meet regulatory requirements with clear data governance

### For Data Teams

* **SQL IDE**: Built-in editor makes view creation easy
* **Cross-Database Joins**: Combine data from multiple sources
* **Testing**: Verify queries before saving as views
* **Organization**: Keep views organized in projects

### For Developers

* **No Custom Code**: Define views with SQL, no integration code needed
* **Standard SQL**: Use familiar SQL syntax
* **Fast Iteration**: Update views and see changes immediately
* **Multiple Tools**: Create different tools on the same view

## Next Steps

Ready to create your first view?

* [SQL IDE Basics](/learn/creating-data-views/sql-ide-basics) - Learn how to use the SQL IDE
* [Writing Your First View](/learn/creating-data-views/writing-your-first-view) - Step-by-step guide to creating a view
* [Cross-Database Joins](/learn/creating-data-views/cross-database-joins) - Join data across multiple sources
* [View Best Practices](/learn/creating-data-views/view-best-practices) - Optimize your views

<Card title="Start Creating Views" icon="code" href="/learn/creating-data-views/sql-ide-basics">
  Learn how to use the SQL IDE to create your first view
</Card>