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The data dictionary is a textual list of all concepts that are defined during the analysis. The purpose of the data dictionary is to define a vocabulary that is common to all the members of the development team and to the customers and users of the system.

A data dictionary is used to catalog and communicate the structure and content of data, and provides meaningful descriptions for individually named data objects.

Data dictionary contents can vary but typically include some or all of the following: A listing of data objects (names and definitions) Detailed properties of data elements (data type, size, nullability, optionality, indexes) Entity-relationship (ER) and other system-level diagrams.

A good example of a data dictionary is the one used by ORNL (Oak Ridge National Laboratory). ORNL maintains this dictionary as a PDF and it resembles a detailed index at the end of a book. The document provides basic information (entry type and description) on each entry, called a variable.

The Data Dictionary in Analysis Workspace helps both users and administrators keep track of and better understand the components in their Analytics environment. Analytics administrators are responsible for curating information about each component in the Data Dictionary to make it available to users.

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.

A Data Dictionary is a collection of names, definitions, and attributes about data elements that are being used or captured in a database, information system, or part of a research project.

Data dictionary is also a business analysis technique featured in the BABOK Guide because it provides the development team with the information to structure and design databases that conform to project requirements.