DATA ADMINISTRATION VS. DATABASE ADMINISTRATION

http://www.tdan.com/i002fe07.htm

IRM: DATA ADMINISTRATION VS. DATABASE ADMINISTRATION
Anne Marie Smith, LaSalle University

Throughout the history of Information Resource Management, there have been questions surrounding the necessity for multiple disciplines within the IRM domain. Many organizations do not recognize the essential differences between Data Administration and Database Administration. As a result, there exists much confusion over the roles of Data Administration and Database Administration, and their respective responsibilities. Each discipline is necessary for the proper management of the corporate resource of information, but these activities should never be combined in one person or sub-group. Each discipline requires different skills, training and talents, therefore, most people do not make a successful transition from one discipline to the other. Data Administration and its sub disciplines: Data Modeling, Data Definitions, Planning and Analysis, is a relative newcomer to the field of data processing. It is only within the last 10-15 years that the industry has given serious consideration to the logical management and control of information as a corporate resource. There is a lack of understanding of the purpose and objectives of Data Administration even among experienced data processing professionals.

Following is a chart of the major responsibilities of Data Administration and Database Administration:

Data Administration - Logical Design

Perform business requirements gathering
Analyze requirements
Model business based on requirements (conceptual and logical)
Define and enforce standards and conventions (definition, naming, abbreviation)
Conduct data definition sessions with users
Manage and administer meta data repository and Data Administration CASE (modeling) tools
Assist Database Administration in creating physical tables from logical models
Database Administration - Physical Design / Operational

Define required parameters for database definition
Analyze data volume and space requirements
Perform database tuning and parameter enhancements
Execute database backups and recoveries
Monitor database space requirements
Verify integrity of data in databases
Coordinate the transformation of logical structures to properly performing physical structures
Perhaps more than any other of the discrete disciplines within IS, Data Administration requires a concrete grasp of the real business the company is in, not just the technical aspects of interaction with a computer. Frequently, a DBA or systems programmer is arguably portable from one industry to another, with minimal retraining as long as the technology remains constant. A DA, on the other hand, has much to learn in an unfamiliar industry to be truly effective. Having an impact on data design and information management requires an understanding of the goals, objectives and tactics of the organization and its core industry (insurance, pharmaceuticals, banking, etc...). Logical Modeling is part of the Data Administration function, and is a full-time responsibility for those involved in a major development or enhancement project. It is frequently augmented by other data administration functions, such as developing data element definitions and managing the models and associated items in a meta data repository. One role of data administration is to advocate the planning and coordination of the information resource across related applications and business areas. By doing so, the amount of data sharing can be maximized, and the amount of design and data redundancy can be minimized.

One way data administrators (also called "data analysts") can assist in making data sharable and consistent across applications is to use the techniques of logical data modeling. Logical data design is a specialty that requires its own specialists. Developers and database administrators are not trained in logical data modeling, and should not be expected to perform this specialized task. The overall objective of Data Administration is to plan, document, manage and control the information resources of an entire organization. The main objective of Data Administration is to integrate and manage corporate-wide information resources. This integration can be achieved by a combination of refined skills and techniques, proper use of Data Administration tools such as a meta data repository and CASE (modeling) products, and logically designed data structures.

In the final analysis, the coordination of Data Administration and Database Administration skills, talents, roles and responsibilities will enable an organization to realize the goal of proper management of its information resource.