Data dictionaries are metadata repositories that contain information about the definition and naming of data assets to support data engineering operations. This definition includes names, settings, and other attributes about the data assets part of a particular database or involved in a given data pipeline. The data dictionary provides a high-level understanding of these elements to provide interpretation and guidance to the stakeholders and help define the scopes and rules of application for each of these data assets.
Data dictionaries help avoid possible inconsistencies or conflicts about data assets in the context of a project, allow for straightforward definition convention for the components involved, and enforce consistency for roles and uses of each of the data elements. Organizations can also use data dictionaries in combination with data catalogs to analyze data operations, obtain insight, and more easily enforce standards. Data Dictionaries may also hold centralized definitions of the terms used to define the data assets and their relationships and metadata about the origin, usage, and data schema.
Data Dictionaries are closely related to relational databases and data warehouses, and database management systems. They can be an integral component to define the database structure or middleware that extends the native dictionary of a database management system.
Typical contents of data dictionaries
- Data asset name
- Format types
- Relationships with other data entities and assets
- Reference data
- Data quality rules
- A hierarchy of the elements composing the data asset (and where it’s contained)
- The location of the datastore
Most of the metadata in data dictionaries focuses on high-level business attributes of the data assets. They are commonly used to communicate and interact between business stakeholders and technical users of the data assets. This way, business stakeholders can ensure that information, contents, and format are according to expectations and requirements. It is also frequently used to help define requirements on projects that require data pipelines or products to be developed.
Active vs. Static Data Dictionaries
Data Dictionaries can either be passive or active. Active Data Dictionaries are dictionaries bound to a specific data repository and get automatically updated by the database management system whenever an event occurs. On the other hand, passive data dictionaries aren’t bound to any specific database and must be manually updated to prevent metadata from being out of sync.
Visit our complete guide to data dictionary, as part of our data management guide
Data Classification with Satori
Satori provides a different approach to data classification. With Satori, data is continuously discovered and classified, instead of performing ad-hoc scans.