The terms business glossary and data dictionary refer to two different artifacts used by data-driven companies to make more effective use of data and information. This post will look at the differences between these two entities and tools to synchronize them to improve their effectiveness.
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A business glossary is a collection of business terms and definitions, documented to ensure business terms are used consistently. They provide a standardized internal vocabulary regarding an organization’s data resources and inform the wider data governance initiative.
When everyone in the company is using the same data definitions, organizations can use information resources more efficiently.
Developing a business glossary helps organizations in:
A business glossary is meant to be used by everyone in an organization. Technical and non-technical personnel can consult the glossary to ensure they are using data terms correctly.
A data dictionary is a compilation of data and its metadata including detailed information and descriptions of the data itself such as its format. It also defines the relationships between the data elements as well as their source and how they are used. It’s a more technically-oriented document than a business glossary. However, data dictionaries reference the business glossary, and should be built in line with vocabulary established within the glossary.
Data dictionaries can be defined as being either active or passive.
An active data dictionary is built into most database management systems. It is accessible to database users through system tables or views and is updated automatically whenever a database schema is updated. No manual maintenance is required with an active data dictionary.
A passive data dictionary is separate from a database and changes in database structure need to be applied manually or with dedicated software tools.
Data dictionaries benefit data-driven organizations, supporting them in:
Business glossaries and data dictionaries are both important entities that help organizations use data efficiently. The terms are sometimes used interchangeably but they have substantial differences that make them appropriate for serving different needs.
Business terms and concepts from across the organization
Physical data assets from a specific data source
Defining a common enterprise data vocabulary and understanding basic business concepts
Gaining an understanding of data resources and databases
A list of business terms and definitions
A list of datasets, tables, fields, and columns
One business glossary exists for each organization
A separate data dictionary is created for every data source
Data modeling, database design
The business as a whole
The business’s IT department and database team
A data catalog is a centralized inventory of enterprise data. It utilizes a complete business glossary and data dictionary to help users locate and access the data they need, and understand its data lineage, metadata and use.
A functioning and effective data catalog must be dynamic, meaning that changes to one element of the data catalog are automatically reflected elsewhere.
For example, as an asset is created in the data dictionary it must be analyzed and each field mapped back to a business term in the business glossary. Changes to the metadata of an asset should be reflected in changes to the business glossary also.
Creating and managing a data catalog can be a time consuming manual task.
Fortunately, organizations can now benefit from automations and synchronizations that help ease the burden.
ER/Studio enables organizations to efficiently create and manage business glossaries by harvesting business terms directly from logical data models. Now, the capabilities of ER/Studio are enhanced with a purpose-built integration between ER/Studio and Collibra.
Data catalogs help organizations enable and/or improve data democratization throughout the enterprise.
ER/Studio’s data modeling and collaboration features integrated with the Collibra data intelligence cloud help create a truly dynamic data catalog and a unified data ecosystem. By integrating ER/Studio’s business glossary with Collibra, organizations can:
ER/Studio and Collibra working together forms a collaborative, unified data ecosystem between data architects and data stewards. This has the following benefits:
More on the ER/Studio Collibra integration can be found in this solution brief.
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