Data Architecture basically deals with designing and constructing data resource. Data Architecture provides methods to design, construct and implement a fully integrated, business-driven data resource that include real world objects and events, onto appropriate operating environments. Data Architecture also covers data resource components.

Data architecture is one of the pillars of Enterprise Architecture. The other pillars are the Application Architecture, Business Architecture and Integration Architecture. The Data Architecture pillar is the definition or blueprint of the data design which will be used in achieving the implementation of a physical database.

The data architecture can be compared to a house design where all the descriptions of the house structure to be built – from the choice of materials, sizes and style of the rooms and roofing, lay out of the plumbing and electrical structures – are described in the blueprint.

In the same manner, the data architecture describes the way data will be processed, stored and used by the organization that will use it. It lays out the criteria on processing operations including the whole flow of the system.
Data architecture falls into the realm of work of data architects. These professionals define the target state, make developmental alignments and then once the data architecture is implemented, data architects make whatever enhancements tailored to the needs and one in the spirit of the original blueprint.

Designing a data architecture is a complex process because this will involve relating abstract data models to real life business activities and entities before implementing the database design and finally setting up the IT hardware infrastructure. If the data architecture is not stable or robust, a failure at one point can save a wave of failures that can cause the whole system to breakdown and result in a lot of monetary loss to the organizations.

The data architecture breaks down subjects into atomic level and then builds them up again to the desired form during the definition of the target state phase. In breaking the subject, there are three traditional architectural processes to be considered. The Conceptual aspect represents all the business entities and its related attributes. The Logical aspect represents the entire logic of the entity relationships. The Physical aspect is the actual data mechanism for particular types of functionalities.

The general framework of the data architecture takes into consideration three vast aspects of the whole information system.

The first is the physical data architecture which is focused on actual tangible hardware elements. Depending on the bulk of data to be processed and the number of data consumers who may be accessing the data warehouse simultaneously, investment in physical data architecture includes buying top of the line computer servers, routers, and other network paraphernalia.

The second aspect pertains to the elements of the data architecture. For instance, the structure of the administrative section of the implementing company and how data is used within the section should be described in the data architecture to become the basis for data models.

The third aspect pertains to the forces at work with can have various influences and constrains which will potentially affect the design. These forces include economics, business policies, enterprise requirements, technology drivers, and data processing needs.

When all these are considered, implementation of a data warehouse of any information system can be guided accordingly.