Data Dictionary

A data dictionary is a centralized repository that describes the structure, definitions, and attributes of data within a database, system, or data model. It serves as a reference guide, documenting details such as data types, formats, constraints, relationships, and allowed values for each field or entity. Data dictionaries help maintain consistency, improve communication across teams, and support data governance.

Also known as: Metadata repository, schema documentation

Comparisons

• Data Dictionary vs. Database Schema: A schema defines how data is structured and stored, while a data dictionary explains what that structure means.

• Data Dictionary vs. Data Catalog: A data catalog includes metadata and discovery tools for data assets; a data dictionary focuses on technical definitions.

Pros

• Improves clarity: Makes data easier to understand and use correctly across teams.
• Supports quality control: Helps validate and standardize data inputs.
• Enhances governance: Aids in enforcing data policies and regulatory compliance.

Cons

• Needs ongoing maintenance: Can become outdated if not regularly updated.
• Not always user-friendly: Technical definitions may be hard to interpret for non-specialists.

Example

In a customer database, a data dictionary entry for the field email_address might include:

Type: String

Format: Valid email pattern (e.g., [email protected])

Max Length: 100 characters

Nullable: No

Description: Stores the primary contact email of the customer

This allows developers, analysts, and stakeholders to use the field consistently and correctly across applications.