Dictionary Needed Field Document For Free

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.

Data dictionaries provide valuable definitions for the data as well as help data Consumers understand any data asset before delving into the details within that asset. In order for data to be trusted and appropriately used, it must be understood and supported by clear definitions.

Components of a data dictionary 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. Reference data (classification and descriptive domains)

5. Creating your data dictionary Step 1: Pull together your terms. Step 2: Identify important information about each term. Step 3: Document your dictionary. Step 4: Revisit and revise your data dictionary.

A data dictionary is a collection of metadata such as object name, data type, size, classification, and relationships with other data assets. Think of it as a list along with a description of tables, fields, and columns.

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.

Your data dictionary should include information such as the data source name and description, the data element name and description, the data element type and format, the data element value and range, the data element constraint and validation, the data element relationship and dependency, the data element usage and ...