Platform Overview
What is Datalinx?
Datalinx is an AI data refinery. It provides a data integration and analytics platform that helps organizations connect, transform, and unify data from multiple sources into a single, reliable view. It combines visual data mapping tools with AI-powered agents that assist you at every step — from discovering your source data to monitoring data quality in production.
Who is Datalinx for?
Datalinx is designed for data teams, analytics engineers, and business analysts who need to:
- Connect to databases and cloud warehouses (Snowflake, Databricks, PostgreSQL, etc.)
- Map and transform source data into clean, unified target schemas
- Resolve customer identities across devices, channels, and platforms
- Build and monitor data pipelines without writing complex code
- Get AI-assisted insights from their data
- Create unique audiences and deliver them directly to the activation platform.
How the Platform is Organized
When you log into Datalinx, you'll see a vertical icon sidebar on the left edge of the screen. The platform is organized into four main sections:
| Section | What It's For |
|---|---|
| Dashboard | Your workspace overview — metrics, progress, and saved dashboards |
| Explore | Query your data, review AI-generated insights, and activate audiences. The first tab in this section is also called "Explore" — it's your SQL query workspace. |
| Configure | The data engineering workflow — discover sources, design targets, map fields, test, and monitor |
| Foundations | Define your semantic layer — business entities, data types, metrics, business logic, and identity rules |
Each section contains multiple tabs. Clicking a section icon in the sidebar opens that section, and you'll see the available tabs along the top of the content area.
The AI Agent Panel
On the left side of every screen (next to the sidebar), you'll see an AI chat panel. This is your Datalinx agent — an AI assistant that understands your data and can help you work through tasks conversationally.
The agent automatically switches depending on which section you're in:
| Section | Agent | What It Helps With |
|---|---|---|
| Dashboard & Explore | Analysis Agent | Writing queries, generating insights, answering business questions |
| Configure | Pipeline Agent | Discovering sources, creating mappings, configuring tests, troubleshooting pipelines |
| Foundations | Foundations Agent | Defining entities, scanning schemas, building your semantic model |
You can type questions or instructions in natural language. The agent can execute actions on your behalf (like creating a mapping or running a query), and it will ask for your approval before making changes.
Typical Workflow
A typical Datalinx initial configuration follows this flow:
1. Create Workspace → Set up a new project and connect to your data sources
2. Discover → Let the AI scan your source tables and understand what data you have
3. Design → Define or import your target schema (what the output should look like)
4. Map → Connect source fields to target fields, add transformations
5. Test → Validate that your mappings produce correct results
6. Monitor → Track data quality, set up alerts, schedule pipeline runs
The Foundations module runs alongside this workflow — it's where you define the business meaning of your data, which ensures you are always working within the right context for your business.