Lookup Table

Welcome to the Lookup Tables section. This section provides comprehensive guidance on how to effectively utilize this powerful feature for managing reference data within your decision-making processes

What Is a Lookup Table?

A Lookup Table is a structured way to store and retrieve reference data using a key-value approach. Unlike Decision Tables that evaluate conditions to produce results, a Lookup Table acts as a data repository where each row is uniquely identified by a primary key, allowing fast and efficient data retrieval.

Think of it as a database table or dictionary that your rules can query to fetch values. For example:

• Product Catalog: Look up product details by SKU or product code

• Pricing Tables: Retrieve prices based on product ID or tier

• Customer Segments: Get customer attributes by customer ID

• Geographic Data: Fetch regional settings by country or postal code

• Configuration Settings: Store application parameters indexed by setting name

Lookup Table Overview

When to Use Lookup Tables

Lookup Tables are ideal when you need to:

• Store reference data that your Decision Tables, Decision Trees, or Flows need to query

• Manage large datasets that would be impractical to maintain within a Decision Table

• Centralize data used across multiple rules

• Import/export data easily via CSV or XLSX

• Maintain data integrity with primary key uniqueness enforcement

Lookup Tables vs. Decision Tables

Feature	Lookup Table	Decision Table
Purpose	Store and retrieve reference data	Evaluate conditions and return results
Structure	Primary key + data columns	Condition columns + Result columns
Logic	Simple key-based lookup	Complex conditional logic
Best for	Static reference data	Business rules with if-then logic
Scalability	Optimized for large datasets	Best for moderate row counts

What You Can Find in This Section

Lookup Table Designer

Learn how to create and edit Lookup Tables using the visual designer

Using Lookup Tables in Rules

Query Lookup Tables from Decision Tables, Trees, and Flows.

Data Import & Export

Import data via CSV, XLSX or JSON.

Quick Start Example

Here's a simple example of a Product Pricing lookup table:

Columns:

Column Name	Alias	Primary Key
Product Code	product_code	✓
Product Name	product_name
Price	price
Category	category

Sample Data:

Product Code	Product Name	Price	Category
SKU-001	Widget Pro	29.99	Electronics
SKU-002	Gadget Plus	49.99	Electronics
SKU-003	Tool Basic	15.00	Hardware

When you query this table with "primaryKey" = "SKU-001", you receive all the associated values for that row.

Key Concepts

Primary Key

Every Lookup Table must have exactly one column designated as the primary key. This column:

• Must contain unique values — no duplicates allowed

• Cannot contain empty values

• Is used to index and retrieve rows efficiently

• Is pinned to the left side of the table for easy identification

Columns

Lookup Table columns define the structure of your data:

• Name: Human-readable label displayed in the header

• Order: Position of the column in the table

Note: Lookup Table Columns are also defined by an Alias - a technical identifier which you should never have to interact with or change.

Rows

Each row in a Lookup Table represents a single record:

• Rows are uniquely identified by the primary key value

• All columns can contain data or be left empty (except the primary key)

• Row order is maintained but is not important when it comes to performance