ROLE OF DATA ARCHITECTURE
University of Michigan- Flint
In the early days of computing, technology simply computerized manual processes with greater efficiency. The new organizational context provides input into the data architecture and is the primary tool for the organization and allocation of enterprise data. It enables architects, data modelers, and stakeholders to identify, classify, and scrutinize information requirements across the enterprise, allowing the right priorities for data sharing initiatives. Data architecture states how data are persisted, accomplished, and utilized within an organization. Data architecture is made up of the construction of all business data and its associations to itself and exterior systems. In far too many conditions, the business community must enlist the support of IT to retrieve information due to the community’s inconsistency, lack of intuitiveness, or other factors. The aim of any architecture should reveal how the components of the construction will be suitable together and how the system will acquaint and advance over time.
Role of Data Architecture
Data architecture defines how data is warehoused, managed, and used in a system. It establishes mutual strategies for data operations that make it probable to predict, model, scale, and control the
flow of data in the system. This is even more important when system components are developed
by or acquired from different outworkers or sellers.
A data architecture should set data morals for all its data schemes as a idea or a model of the ultimate interactions between those data systems. Data integration, for example, should be contingent upon data architecture standards since data combination requires data connections between two or more data systems. A data architecture, in part, defines the data structures used by a corporate and its computer applications software.
Crucial to apprehending the goal state, Data Architecture describes how data is processed, stored, and operated in an information system. It provides values for data processing operations so as to make it possible to design data flows and also control the flow of data in the system.
The data architect is typically responsible for defining the goal state, aligning during development and then following up to ensure enrichments are done in the spirit of the original proposal.
Throughout the description of the mark state, the Data Architecture pauses a subject down to the microscopic level and then builds it back up to the looked-for form. The data architect breaks the subject down by going through 3 traditional architectural processes:
· Conceptual – characterizes all business entities.
· Logical – signifies the logic of how entities are related.
· Physical – the realization of the data mechanisms for a specific type of functionality.
Figure 1: Diagram of data architecture
Objective of the Three Level Architecture
The objective of the three-level architecture is to detach each user’s view of the database from the Way the database is physically represented. There are several reasons why this separation is required:
• Each user should be able to access the identical data, but have a different personalized view of the data. Each user should be able to change the way he or she views the data, and this change should not affect other users.
• Users should not have to deal directly with physical database storage facts, such as indexing or hashing. In other words, a user’s interaction with the database should be self-governing of storage considerations.
• The Database Administrator (DBA) should be able to alter the database storage constructions without upsetting the user’s views. The core structure of the database should be unaffected by changes to the physical aspects of storage, such as the changeover to a new storage device. The DBA should be able to change the database design without affecting other people or the users.
External Level or View level
It is the users’ view of the database. Each user is relevant to this level of the database. The level closest to the user seems to be the external or the view level. This level deals with the way in which individual user’s data. Individual users are given different views according to the user’s condition. A view involves only those portions of a database which are of apprehension to a user. Therefore, identical database can have diverse views for diverse users. External level is also known as the view level. In addition, different views may have diverse illustrations of the same data. For example, one user may sight birth dates in the form (day, month, year), while another may sight birthdates as (year, month, day).
Conceptual Level or Logical level
It is the community sight of the database. What data is stored and the relationship between the data is described here. The conceptual level is the middle level in the three-level architecture. This level contains the rational structure of the complete database as seen by the DBA. It is a broad view of the data necessities of the organization that is autonomous of any storage contemplations. The conceptual level represents:
• All units, their attributes, and their relationships. The information of the item stored in the database is known as an entity. For instance, in teacher database the entity is teacher. For example, in case of teacher database Name, Class, Subject, Address etc. are attributes of entity teacher.
• The limitations on the data;
• Semantic evidence about the data;
• Safety and honesty information.
The conceptual level supports each external view which needs to be in the conceptual form However, in this level storage dependent details are not expected. For instance, the description of an entity should contain only data types of attributes (for example, integer, real, character) and their, but not any storage considerations, such as the number of bytes occupied. Conceptual level is also known as the, logical level. (Whatisdbms.com)
Internal level or Storage level
It is the physical illustration of the database on the computer. How the data is stored in the database is depicted here. The internal level is the one that concerns the way the data are physically warehoused on the hardware. The internal level shelters the physicalimplementation of the database to accomplish optimal runtime performance and storage space consumption. It covers the data structures and file administrations used to store data on storage devices. It lines with the operating system access approaches to place the data on the storage devices, build the guides, repossess the data, and so on.
The internal level is concerned with such things as:
• Storage space allocation for data and indexes;
• Record descriptions for loading
• Record placement;
• Data compression and data encryption techniques.
Logical representation of the database as a complete will be considered in the theoretical view. Similarly, there will be only one internal or physical view, representing the total database, as it is physically stored.
A documented understanding of the Enterprise data architecture is a vital pre-requisite to many common IS and business enhancement initiatives. The appropriate models are relatively distinct from both comprehensive system models and advanced business models.
2.) “An Enterprise Information System Data Architecture Guide”, Grace Alexandra Lewis
Santiago Comella-Dorda, Pat Place, Daniel Plakosh, Robert C. Seacord, October 2001, Carnegie Mellon, Software Engineering Institute.
3.) Modelling the Enterprise Data Architecture, Copyright © Andrew K. Johnston and Richard Wiggins, 2003