Core Concepts

Overview

Rowbase is built around a few core concepts that work together to help you manage and transform your data.

Organizations

An Organization is the top-level container for all your work in Rowbase. It represents your company or team.

Each organization has its own billing, member management, and settings.

Key features:

Invite team members with role-based access (Admin, Member, Viewer)
Configure SSO and security settings
Manage API keys and integrations

Projects

A Project groups related datasets together. Think of it as a folder for a specific initiative or workflow. Examples:

“Q1 Marketing Campaign” - contains lead lists, email performance data
“Customer Data Cleanup” - contains raw and cleaned customer records
“Sales Pipeline” - contains deal data, forecasts, and metrics

Datasets

A Dataset is a structured collection of data, similar to a spreadsheet or database table.

Structure
Features

Each dataset has:

Columns - Named fields with specific data types (text, number, date, boolean)
Rows - Individual records in your data
Schema - The structure definition that validates your data

Data Types

Type	Description	Example
`text`	String values	”Hello World”
`number`	Numeric values (integers and decimals)	42, 3.14
`boolean`	True/false values	true, false
`date`	Date and datetime values	2024-01-15
`json`	Nested JSON objects	`{"key": "value"}`

Operations

Operations are transformations you apply to datasets. They’re non-destructive - the original data is preserved and you can always undo or modify operations.

Filter

Remove rows that don’t match specified conditions.

Filter: status = "active" AND created_at > "2024-01-01"

Parse & Transform

Convert text to numbers, dates, booleans, and more.

Parse: "$1,234.56" → 1234.56

Use AI

Generate content, detect headers, and enrich data with AI.

Input: product description → Output: category

Rename Columns

Change column names for clarity.

Rename: "col1" → "customer_name"

Join & Union

Combine data from multiple tables.

Validate

Ensure data quality with constraints and quarantine rules.

Operation Pipeline

Operations are applied in sequence, creating a transformation pipeline:

You can reorder, edit, or remove any operation in the pipeline at any time.

Formulas

Formulas let you create computed columns using spreadsheet-like expressions.

Syntax

Reference other columns using their names:

UPPER(first_name) + " " + UPPER(last_name)

Available Functions

Text
Math
Logic
Date

UPPER(text) - Convert to uppercase
LOWER(text) - Convert to lowercase
TRIM(text) - Remove whitespace
CONCAT(a, b, ...) - Join strings
LEFT(text, n) - First n characters
RIGHT(text, n) - Last n characters

SUM(a, b, ...) - Add values
AVG(a, b, ...) - Average values
MIN(a, b, ...) - Minimum value
MAX(a, b, ...) - Maximum value
ROUND(num, decimals) - Round number
ABS(num) - Absolute value

IF(condition, then, else) - Conditional
AND(a, b, ...) - All true
OR(a, b, ...) - Any true
NOT(value) - Negate
ISBLANK(value) - Check if empty

NOW() - Current datetime
TODAY() - Current date
YEAR(date) - Extract year
MONTH(date) - Extract month
DAY(date) - Extract day
DATEDIFF(a, b, unit) - Difference between dates

Next Steps

Datasets

Deep dive into dataset features

Operations

Learn about all available operations

Formulas

Master formula syntax and functions

API Integration

Automate with the Rowbase API

Getting Started

Core Features

Integrations

Overview

Organizations

Projects

Datasets

Data Types

Operations

Operation Pipeline

Formulas

Syntax

Available Functions

Next Steps

Datasets

Operations

Formulas

API Integration

​Overview

​Organizations

​Projects

​Datasets

​Data Types

​Operations

​Operation Pipeline

​Formulas

​Syntax

​Available Functions

​Next Steps

Datasets

Operations

Formulas

API Integration

Overview

Organizations

Projects

Datasets

Data Types

Operations

Operation Pipeline

Formulas

Syntax

Available Functions

Next Steps