Enterprise Data Architecture (EDA)

Definition - What does Enterprise Data Architecture (EDA) mean?

Enterprise data architecture (EDA) refers to a collection of master blueprints designed to align IT programs and information assets with business strategy. EDA is used to guide integration, quality enhancement and successful data delivery.

EDA is part of the overall enterprise architecture, which has several integrated aspects, including hardware, applications, business processes, technology choices, networks and data.

[Free eBook] Essential Guide to Machine Data: Network Machine Data | DOWNLOAD TODAY

Techopedia explains Enterprise Data Architecture (EDA)

The EDA model is comprised of different layers that provide a strong foundation for strategic endeavors, such as:

A data strategy that outlines the objectives of business for the improvement of data collection and data use Improvements in the business process
Decisions on the potential future of new and modified solutions
Data warehousing, integration and reporting initiatives

Enterprise data architecture is explained mainly by models at four different levels:

High-Level Data Model (HLDM): Constitutes a collection of HLDMs that describe business data through a conceptual viewpoint independent of any present realization by real systems. The HLDM consists of a standard UML class model of the primary data items and their relationships; a superset of business features, such as semantics, universal constraints and syntax.
Realization overviews: Describes the relationships between the real vital data objects of the present or planned systems and the conceptual units of the HLDM. This shows the way in which conceptual units are realized by actual units.
Source and consumer models: Demonstrates the correlations between various realizations of the same data items, diverse organizational custodians of data elements and the way in which modifications are circulated around different systems.
Transportation and transformation models: Explains the way in which data in the implementation systems changes when moved among systems. They include attribute structure and physical class of system interfaces. This model also depicts the realization of the HLDM within the interface mechanisms, including a backbone or an enterprise application integration (EAI) hub.

EDA advantages are as follows:

Helps gain a better understanding of data
Is a vital factor for developing and implementing governance that supports a data strategy
Guides developments across systems, such as common reporting, enterprise application integration (EAI) and data warehousing initiatives.