Studio Onboarding — HireLens Docs

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# Studio Onboarding Guide

This guide walks you through building your first pipeline from scratch, step by step.

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## Opening Studio

Navigate to **[Analytics Studio](/analytics/studio)**. You will see:

- **Left panel** — Node palette with draggable node types
- **Center** — The canvas where you build pipelines
- **Top toolbar** — Run button, templates, and controls
- **Bottom panel** — Results appear here after running

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## Step 1: Add a Data Source

Every pipeline starts with a **Source** node. This determines where your data comes from.

### How to add:
1. In the left palette, find the **Source** section (green nodes)
2. **Drag** "Vacancies" onto the canvas

The node appears on the canvas with a green header showing "Vacancies".

> **Tip:** You can also use "Companies" as a source for company-centric analyses.

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## Step 2: Add Filters (Optional)

Filters narrow your dataset before analysis. Drag filter nodes from the **Filter** section (blue nodes).

### Available filters:

| Filter | What It Does | Example |
|--------|-------------|---------|
| **By Role** | Keep only specific roles | Backend, Frontend |
| **By Seniority** | Filter by experience level | Senior, Lead |
| **By Domain** | Filter by industry | DeFi, Gaming |
| **By Salary** | Min/max salary range | $100K - $200K |
| **By Date** | Recent signals only | Last 30 days |
| **By Score** | Quality threshold | Score 7+ |
| **By Location** | Location type | Remote only |

### How to connect:
1. Drag a filter node onto the canvas
2. **Click** the output port (right side) of the Source node
3. **Drag** to the input port (left side) of the Filter node
4. Release — a connection line appears

You can chain multiple filters: Source then Filter 1 then Filter 2.

### Configuring a filter:
Click on the filter node. A configuration panel appears on the right where you can set the filter criteria.

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## Step 3: Group Your Data

To compute metrics like counts or averages, you need to **group** your data first.

1. Drag a **Group By** node from the Aggregation section (purple)
2. Connect it to your last filter (or directly to the source)
3. Click it to configure — select which field to group by

### Common groupings:
- `role` — Group by job role
- `seniority` — Group by experience level
- `company_name` — Group by company
- `domain` — Group by industry vertical
- `location_type` — Group by Remote/Office/Hybrid
- `employment_type` — Group by Full-time/Part-time/Contract

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## Step 4: Add Aggregations

After grouping, add an **Aggregate** node to compute metrics.

1. Drag an **Aggregate** node and connect it after Group By
2. Click to configure:
   - **Function** — COUNT, AVG, SUM, MIN, MAX
   - **Field** — Which field to aggregate (e.g., `salary_min`)
   - **Alias** — Name for the result column (e.g., `avg_salary`)

### Examples:
- COUNT on `id` gives you the count of vacancies per group
- AVG on `salary_min` gives average minimum salary per group
- MAX on `score` gives highest quality score per group

> **Important:** The alias you set here becomes a column name you can use in Sort and Chart nodes downstream.

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## Step 5: Sort and Limit

### Sort
1. Drag a **Sort** node and connect after Aggregate
2. Click to configure — the dropdown **automatically shows available columns** from your upstream Group By and Aggregate nodes
3. Choose ascending or descending order

### Limit
1. Drag a **Limit** node to cap the number of results
2. Set the maximum rows (e.g., 10 for a "Top 10" analysis)

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## Step 6: Add an Output

The output node determines how you see results.

### Chart
1. Drag a **Chart** node from the Output section (yellow)
2. Connect it to your pipeline
3. Click to configure:
   - **Chart type** — Bar, Line, Doughnut, Polar Area, Radar
   - **Label column** — What goes on the X axis (e.g., `role`)
   - **Value columns** — What gets plotted (e.g., `count`, `avg_salary`)

### Table
Drag a **Table** output for a sortable data grid.

### Export CSV
Drag an **Export** output to download results as a spreadsheet.

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## Step 7: Run the Pipeline

Click the **Run Pipeline** button in the top toolbar.

The platform:
1. Validates your pipeline structure
2. Sends it to the backend
3. Generates an optimized SQL query
4. Executes against the database
5. Returns results to your output node

Results appear in the bottom panel within seconds.

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## Using Templates

Click **Templates** in the toolbar to load pre-built pipelines:

- **Salary by Role** — Average salaries broken down by position
- **Hiring Trends** — Monthly vacancy volume over time
- **Top Companies** — Most active hirers
- **Skills Demand** — Most requested technologies
- **Remote vs Office** — Location type distribution
- **Seniority x Salary** — How compensation scales with experience
- **Domain Overview** — Industry sector breakdown

Templates load a complete pipeline — you can run it immediately or modify it.

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*Continue to [Node Reference](/docs/studio-nodes) for detailed documentation of every node type.*

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