An Enterprise Data Model is a representation of single definition of data of an enterprise is and the representation is not biased on any system application. It independently defines how the data is sources, stored, processed or accessed physically.
Enterprise Data Model gives overall picture of an industry perspective by offering an integrated blueprint view of entire data that is produced as well as consumed in all departments of an enterprise or an organization. It helps to resolve all potential inconsistencies and parochial interpretations of the data used
It can also be a framework or an architectural design of data integration which enables the function of identifying all shareable and/an redundant data across functional and organizational boundaries. It serves to minimize data redundancy, disparity, and errors; core to data quality, consistency, and accuracy.
With Enterprise Data Model being a data architectural framework, the business enterprise will have some sort of starting point for all data system designs. Its theoretical blueprint can provide for provisions, rules and guide in the planning, building and implementation of data systems.
In the area of enterprise information system, the Operational Data Store (ODS) or Data Warehouse (DW) are two of the largest components which need carefully designed enterprise data model because data integration is the fundamental principle underlying any such effort and a good model can facilitate data integration, diminishing the data silos, inherent in legacy systems.
As the name implies, the very core of an Enterprise Data Model is about the data, regardless of where the data is coming from and how it will be finally used. The model is meant primarily to give clear definitions on how come up with efficient initiatives in the aspects of Data Quality, Data Ownership, Data System Extensibility, Industry Data Integration, Integration of Packaged Applications and Strategic Systems Planning.
The process of making an enterprise model typically utilizes a top down bottom up approach for all designs of the data systems including the operational data store, data marts, data warehouse and applications. The enterprise data model is built in three levels of decomposition and forms a pyramid shape.
The first to be created is Subject Area Model which sits on top of the pyramid. It expands down to create the Enterprise Conceptual Model and finally the Enterprise Conceptual Entity Model is created and occupies the base part of the pyramid. The three models are interrelated but each of them has its own unique purpose and identity.
A fundamental objective of an Enterprise Subject Area Model is segregating the entire organization into several subjects in a manner similar to divide and conquer. Among the aspects of this level are Subject Areas, Subject Area Groupings, Subject Area Data Taxonomy and Subject Area Model Creation.
The Enterprise Conceptual Model, the second level in the pyramid, identifies and defines the major business concepts of each of the subject areas. This model is high level data model having an average of several concepts for every subject area. These concepts have finer details compared to the subject area details. This model also defines the relationships of each concept.
The Enterprise Conceptual Entity Model represents all things which are important to each business area from the perspective of the entire enterprise. This is the detailed level of an enterprise data model which each of the concept being expanded within each subject area. It is also in this level that the business and its data rules are examined, rather than existing systems so as to create the major data entities, the corresponding business keys, relationships and attributes.