A data dictionary which is also known as a metadata repository is used to describe what data elements are and communicate their meaning and values to the stakeholders.
Data dictionary are usually used in combination with data models and can be managed automatically or manually.
Data dictionaries are made up of some components which include:
1. Data Elements: A data dictionary has descriptions of the data elements and shows how these elements could be merged into merged data elements.
2. Primitive Data Elements: Data elements are made up of components and to fully understand these components, the following information has to be documented:
• Name: This is the distinctive name for the data element.
• Aliases: these are other names which the stakeholders could call the data element.
• Values/Meanings: these are a list of acceptable values for the data element.
• Description: this is the definition of the data element in the relation of the
solution.
3. Composite Elements: Composite data elements are assembled using data elements, which could include:
• Sequences: this is the necessary arrangement of primitive data elements into the combined structure. For example, a plus sign shows that one element is connected to other elements. for example: Customer Address = Address One + Address two +City + State + Country.
• Repetitions: this would be present if one or more data elements may need to be replicated numerous times.
• Optional Elements: these are elements that may not appear in the composite element.
The data dictionary has both its strengths and its limitations which are:
Strengths
• It ensures that all stakeholders understand the composition and essence of appropriate information.
• A single database of corporate metadata would help standardize data in the organization.
Limitations
• It needs regular maintenance, or the metadata would become outdated or incorrect.
•The database has to be properly maintained to ensure that the information can be quickly and easily accessed.