Conventions

When you’re building a data solution with dozens — or hundreds — of tables, columns, and scripts, consistency makes a real difference. ADL’s conventions capture your project’s standards in one place, and increasingly they don’t just describe the standard — they apply it for you.

What are conventions?

A convention is a named value in your project, organized into groups. Conventions play three roles, from simple to powerful:

1. Naming rules and reference values are plain key/value pairs your team agrees on: prefixes, identifiers, standard names. For example, hub tables are prefixed HUB_, the surrogate key identifier is SK.
2. As template values and patterns, any convention can be exposed to your templates as conventions.YourKey, and its value can itself be a Handlebars pattern (like HUB_{{dataObject.name}}) that’s rendered when used. Templates never hard-code names; they ask the conventions.
3. Standard data items are conventions linked to one or more classifications, turning the convention into a managed column: ADL automatically adds a column named after the convention’s value to every data object carrying that classification, with the right data type, position, and key settings.

Standard data items: conventions that do the work

Every data solution has framework columns that appear on almost every table — an audit trail ID, a record source, load timestamps, checksums, surrogate keys. Maintaining those by hand across hundreds of objects is tedious and error-prone.

With standard data items, the convention is the single source of truth:

• The convention’s value is the column name; per-classification settings define the data type, placement (before or after your business columns), relative order, and whether it’s part of the primary key.
• ADL applies the columns automatically, both when the project loads and whenever conventions change. Change the audit column’s name or type once, and every matching object follows.
• Columns are kept in three zones: leading standard columns, your business columns, trailing standard columns — so generated tables have a predictable, uniform shape.
• When a convention is deleted, ADL offers to clean up the columns it was managing.
• Metadata Health validates that managed columns sit where their convention prescribes.

Why conventions matter

• When every table and column follows the same pattern, your data solution is easier to understand and navigate.
• Team members can look at any object and immediately understand what it is and where it fits, because the naming is predictable.
• Templates reference conventions instead of hard-coding names, and standard data items maintain framework columns without manual work.
• Standards evolve. When they’re captured as conventions, changing the standard is one edit, not a project-wide refactor.

Working with conventions in ADL

You manage conventions from the Conventions screen. The sample solutions ship with realistic convention sets — naming patterns for Data Vault ensembles, control-framework columns as standard data items, surrogate key definitions — that are worth reading as examples of the idiom.

What’s next?

• Using the App — Conventions covers the screen, the dialog, and the standard data item settings.
• Classifications explains how standard data items target objects through their classifications.
• Templates & Code Generation shows how templates consume conventions.