Dataset Basics

A Dataset defines what data to extract from a web page.

Core Concepts

Concept	Description
Dataset	A named collection of properties to extract
Item Selector	The repeating parent container (e.g., .product-card)
Property	A single field to extract (e.g., title, price)
Record	One row of extracted data (one per matched item)

How Extraction Works

1. RTILA navigates to the page.
2. It finds all elements matching the Item Selector.
3. For each matched element, it extracts all Properties.
4. Each matched element becomes one Record.
5. Records are stored and can be exported or sent to triggers.

Example

Page: A product listing page with product cards.

Item Selector: css=.product-card

Properties:

Property	Selector	Type
title	css=h2	text
price	css=.price	text
link	css=a	attribute (href)
image	css=img	attribute (src)

Result:

title	price	link	image
Product A	$29.99	/products/a	/images/a.jpg
Product B	$49.99	/products/b	/images/b.jpg

Dataset Settings

Setting	Description
Name	Unique name for the dataset
Item Selector	CSS/XPath selector for the repeating container
Parent Dataset	Optional link to a parent dataset
Required Fields	Fields that must have values

Adding a Dataset

In the Visual Builder

1. Open the project in the Visual Builder.
2. Switch to the Data Extraction tab.
3. Click + to add a dataset.
4. Click + to add properties.
5. Use the element picker to select elements.

Via AI

Ask the AI: “Extract all product names and prices from this page.”

Via AI Visual Extraction

Click the wand icon (✨) in the Data Extraction tab.

Multiple Datasets

A project can have multiple datasets. For example:

• products — Product listing data
• reviews — Review data
• metadata — Page metadata

Each dataset is extracted independently and stored separately.

Dataset Previews

The Data Extraction tab shows a live preview of the data. This updates as you modify selectors.

Tip: If the preview shows “No matching data found,” your selectors may not match any elements. Use the element picker to fix them.