Naming Conventions

When you’re building a data solution with dozens — or hundreds — of tables, columns, and scripts, consistent naming makes a real difference. ADL’s conventions feature helps you define and enforce naming standards across your project.

What are conventions?

Conventions in ADL are naming rules that you set up for your project. They define patterns for how things should be named — tables, columns, schemas, and other elements of your data solution.

For example, you might define conventions like:

• Staging tables should be prefixed with stg_
• Hub tables in a Data Vault should be prefixed with hub_
• All column names should use snake_case
• Audit columns should follow a specific naming pattern

Conventions help you stay consistent without having to remember every naming rule yourself. When you and your team agree on a standard, you can capture it in ADL and rely on it throughout the project.

Why conventions matter

• Consistency — When every table and column follows the same naming pattern, your data solution is easier to understand and navigate.
• Collaboration — Team members can look at any object and immediately understand what it is and where it fits, because the naming is predictable.
• Automation — Templates can reference conventions to generate correctly named output automatically, without hard-coding names into each template.
• Documentation — A clear naming standard makes your data solution self-documenting to a degree — the names themselves carry meaning.

Working with conventions in ADL

You manage conventions from the Conventions screen in the app. Here you can create, edit, and review the naming rules for your project.

Conventions work hand-in-hand with templates — when a template generates output, it can reference your project’s conventions to ensure the generated names follow your standards.

What’s next?

• Classifications — Learn about tagging data for compliance and organization.
• Using the App — Conventions — Manage conventions in the ADL interface.