Enterprise and Data Architecture

Enterprise and Data Architecture

Today, most large enterprises live in a data landscape that is highly fragmented and contains significant redundancy. Having evolved over time as a result of mergers and acquisitions, custom application development and the use of packaged applications, the technology supporting this data infrastructure includes multiple database management systems (DBMSs) and various tools for data movement and integration. In addition, a large number of point-to-point interfaces usually ties these fragments together. The end result, when represented graphically, is the classic “spaghetti diagram” of an environment, which is often so complex that no one in the organization can understands it.

ZonTeq Enterprise data architecture offering works with our customers to improve process of managing data across the enterprise with the objective of resolving — or at least minimizing — these issues. By seeking opportunities for simplification, removing unnecessary data movement and fostering semantic, design and technology standards, enterprises can achieve cost savings and establish a more-flexible foundation to support our customers strategic business initiatives.

ZonTeq EDA Model

Our 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

ZonTeq EDA modeling include 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.

Advantages:

·         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.