In some aspects of information technology, a data element is referred to as any named unit of data which may or may not consist of other data items. In many electronic record keeping applications, a data element is a combination of bytes or characters which refer to a separate item of information like name, address and gender.

A data element has a definition done in metadata. The definition may either be a phrase in human readable form or a sentence which is associated with the data element within the dictionary. Having a good data element definition can add greater benefits in such process as mapping of one set of data into another set of data.

Data is the main component of a data warehouse. Most businesses today are heavily reliant on information from a data warehouse. The term data-driven business is very much in use today with the ubiquity of the internet.

Data warehousing is a complex undertaking which very careful planning through several stages of implementation. An active data warehouse has a capacity to search for trends and patterns in evaluation data so that a company can strategize in order to gain competitive edge over its competitors. So in order to gain relevant information from a data warehouse, the data must be well structured.

A data warehouse should be based on a common data architecture which is a formal and comprehensive data planning which is the basis for a common context from which data resources are integrated. The data within the architecture are in turn based on the common data model.

Data modeling is the process of turning data into representations of the real life entities, events and objects that are of interest to the organization. So that the data warehouse can come up with consistent data, a data dictionary should also be set up.

A data dictionary, in technical terms, refers to a set of metadata (metadata is information about a data) which contains definitions and representations of data elements. From the perspective of a relational database management system, data dictionary is a set of tables and views which can be read and never altered as it holds the definition of all data elements used in the data architecture as well as the physical implementation of the database.

The data dictionary, aside from containing the definitions of all data elements, also contains usernames and the corresponding roles and privileges, schema objects, integrity constraints, stored procedure and triggers, information about the general database structure and space allocations.

The way data elements are stored within the database may vary depending on the database design and the relational database management software application. But data elements are always the same in that they are atomic units of data containing identifications such as data element name. A data element should have a clear definition and a representation of one or more terms.

Data elements can be used depending on the application employing them. But their usage can be discovered by inspecting the applications or the data files of the applications through Application Discovery and Understanding which can be done manually or automatically.

The process of Application Discovery and Understanding (ADU) involves analyzing of artifacts of a software application and then determining the structures of the associated metadata in the form of lists of business rules and data elements. After the data elements are being discovered they can be registered in the registry for metadata