What is a Data Dictionary?

A Data Dictionary, also called a Data Definition Matrix, provides detailed information about the business data, such as standard definitions of data elements, their meanings, and allowable values. While a conceptual or logical Entity Relationship Diagram will focus on the high-level business concepts, a Data Dictionary will provide more detail about each attribute of a business concept.

Essentially, a data dictionary provides a tool that enables you to communicate business stakeholder requirements in such a way that your technical team can more easily design a relational database or data structure to meet those requirements. It helps avoid project mishaps such as requiring information in a field that a business stakeholder can’t reasonably be expected to provide, or expecting the wrong type of information in a field.

The Key Elements of a Data Dictionary

A Data Dictionary provides information about each attribute, also referred to as fields, of a data model. An attribute is a place in the database that holds information. For example, if we were to create a Data Dictionary representing the articles here on Bridging the Gap, we’d potentially have attributes for article title, article author, article category, and the article content itself.

A Data Dictionary is typically organized in a spreadsheet format. Each attribute is listed as a row in the spreadsheet and each column labels an element of information that is useful to know about the attribute.

Let’s look at the most common elements included in a data dictionary.

  • Attribute Name – A unique identifier, typically expressed in business language, that labels each attribute.
  • Optional/Required – Indicates whether information is required in an attribute before a record can be saved.
  • Attribute Type – Defines what type of data is allowable in a field. Common types include text, numeric, date/time, enumerated list, look-ups, booleans, and unique identifiers.

While these are the core elements of a data dictionary, it’s not uncommon to document additional information about each element, which may include the source of the information, the table or concept in which the attribute is contained, the physical database field name, the field length, and any default values.

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