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Database - Database is a collection of related data while database management system is a software which is use to access the database.
A database is an accumulation of data, for storage and future use. The database management system would be the software you use to..this is too easy...manage the database. In other words, to search, sort, filter, and retrieve the data, or parts of it, from the database.

Attributes - A quality or characteristic inherent in or ascribed to someone or something.
An object associated with and serving to identify a character, personage, or office: Lightning bolts are an attribute of Zeus.
Grammar. A word or phrase syntactically subordinate to another word or phrase that it modifies; for example, my sister's and brown in my sister's brown dog.

System Analysis - The application of mathematical methods to the study of complex human physical systems. A system is an arrangement or collection of objects that operate together for a common purpose. The objects may include machines (mechanical, electronic, or robotic), humans (individuals, organizations, or societal groups), and physical and biological entities. Everything excluded from a system is considered to be part of the system's environment. A system functions within its environment. Examples of systems include the solar system, a regional ecosystem, a nation's highway system, a corporation's production system, an area's hospital system, and a missile's guidance system. A system is analyzed so as to better understand the relationships and interactions between the objects that compose it and, where possible, to develop and test strategies for managing the system and for improving its outcomes.

The term “systems analysis” is reserved for the study of systems that include the human element and behavioral relationships between the system's human element and its physical and mechanical components, if any. Examples of public policy systems are the federal government's welfare system, a state's criminal justice system, a county's educational system, a city's public safety system, and an area's waste management system. Examples of industrial systems are a manufacturer's production distribution system and an oil company's exploration, production, refining, and marketing system. Examples with physical environmental components are the atmospheric system and a water supply system. The direct transfer of systems engineering concepts to the study of a system in which the human element must be considered is restricted by limitations in the ability to comprehend and quantify human interactions. (Operations research, a related field of study, is directed toward the analysis of components of such systems. Public policy analysis is the term used for a system study of a governmental problem area.) See also Decision theory; Operations research; Systems engineering.

Systems comprise interrelated objects, with the objects having a number of measurable attributes. A mathematical model of a system attempts to quantify the attributes and to relate the objects mathematically. The resultant model can then be used to study how the real-world system would behave as initial conditions, attribute values, and relationships are varied systematically. See also Model theory.

The systems analysis process is an iterative one that cycles repeatedly through the following interrelated and somewhat indistinct phases: (1) problem statement, in which the system is defined in terms of its environment, goals, objectives, constraints, criteria, actors (decision makers, participants in the system, impacted constituency), and other objects and their attributes; (2) alternative designs, in which solutions are identified; (3) mathematical formulation, in which a mathematical description of the system is developed, tested, and validated; (4) evaluation of alternatives, in which the mathematical model is used to evaluate and rank the possible alternative designs by means of the criteria; and (5) selection and implementation of the most preferred solution. The process includes feedback loops in which the outcomes of each phase are reconsidered based on the analyses and outcomes of the other phases. For example, during the implementation phase, constraints may be uncovered that hinder the solution's implementation and thus cause the mathematical model to be reformulated. The analysis process continues until there is evidence that the mathematical structure is suitable; that is, it has enough validity to yield answers that are of value to the system designers or the decision maker. See also Optimization; Simulation.

As originally developed, systems analysis studies have been applied to those areas that are “hard” in that they are well defined and well structured in terms of objectives and feasible alternative systems (for example, blood-bank design, and integrated production and inventory processes). The aim of hard systems analysis is to select the best feasible alternative. In contrast, soft systems are concerned with problem areas that involve ill-defined and unstructured situations, especially those that have strong political, social, and human components. These generally involve public and private organizations (for example, design of a welfare system, and structure and impact of a corporate mission statement). The objectives of soft systems and the means to accomplish them are problematical and, in fact, a systemic view of the problem area is not assumed. The aim of soft systems analysis is to find a plan of action that accommodates the different interests of its human actors.

There is also need for further study of large-scale systems, which by definition are most complex. It is important to find ways to describe mathematically the systems that represent the totality of an industrial organization, the pollution concerns of a country and a continent, or the worldwide agricultural system. These are multicriteria problems with the solutions conflicting across criteria, individuals, and countries. The possibility that such systems may be studied in a computer-based laboratory is very promising. But this challenge must be approached cautiously, with the awareness that the methods and models employed are only abstractions to be used with due consideration of the goals of the individual and society. See also Large systems control theory; Linear system analysis.

Entity Relationships - An Entity-Relationship Model (ERM) in software engineering is an abstract and conceptual representation of data. Entity-relationship modeling is a relational schema database modeling method, used to produce a type of conceptual schema or semantic data model of a system, often a relational database, and its requirements in a top-down fashion.



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