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Systems Analysis > Analysis Process
Analysis Process:
Analysis is applied and used in all fields and subjects, and by many people and team members with the purpose of gaining more understanding, finding answers, solving problems, and as a step towards reaching a decision. In any field, analysis is carried out in steps or stages guided by rules and logics. Analysis approaches may differ with the fields of study or applications but it always preserve its main characteristics and destinations as it applied in a variety of fields as: chemistry, business, computer science, engineering, physics, economics, linguistics, mathematics, music, philosophy, medicine, statistics, and so many others. Definition of analysis can be found in Wikipedia as follows:
Analysis Definition:
"Analysis is the process of breaking a complex topic or substance into smaller parts to gain a better understanding of it. The technique has been applied in the study of mathematics and logic since before Aristotle (384–322 B.C.), though analysis as a formal concept is a relatively recent development.". In the field of business, analysis is defined according to the site business dictionary as :
1. A systematic examination and evaluation of data or information, by breaking it into its component parts to uncover their interrelationships, and this is oposite to synthesis. Another definition can be found as:
2.An examination of data and facts to uncover and understand cause-effect relationships, thus providing basis for problem solving and decision making

Analysis Process SituationSystem view
By examining other definitions and examples of analysis, we conclude that analysis is indeed a process applied as part of overall methods or methodology to a problem or subject or substance, with many commonality between its stages as it applied in various fields.
In information systems, Analysis Process is carried out in various phases of systems development. It is used at early phases in requirements definitions as requirements analysis, then in business analysis, as business area analysis. In feasibility analysis we carry cost benefit analysis and payback analysis, and also risk analysis. In examining the system functions we concentrate on system processes and conduct a thorough process analysis and data analysis through Data Flow Analysis and Object analysis. When we deal with social systems which characterized by its soft problems stake holders analysis becomes an essential step in identifying all those who deal with the system, and with CATEO analysis as outlines by Soft Systems methodology. Also, at this stage Casual Loop analysis may help in defining the interacting feedback loops within the system. These feedback loops are also used to synthesize system behavior and to test its expected performance to make sure that our design for the solution will be satisfactory . Trying to synthesis system structure side by side with each phase of systems development and during the analysis process will guarantee the building of a successful system. Also, the analysis process needs to utilize different types of tools and models as it applied in various fields and applications. Models are used with the two purposes: the first is to help in simplify the analysis procedures as the analysis goes deeper into the problem, and the second it offer means to visu the analysis process itself through its stages with its destination or results
In Analysis we take the system apart to understand how the system works the way it does, but we cannot look to all parts and we are forced to reduce it into a manageable numbers. If we need to diagnose a system and to know why it works the way it deos, we need to look at the larger system to which it work with, or it belong to. This is sysnthesis

The approach of systems thinking is fundamentally different from that of traditional forms of analysis. Traditional analysis focuses on the separating the individual pieces of what is being studied; in fact, the word "analysis" actually comes from the root meaning "to break into constituent parts." Systems thinking, in contrast, focuses on how the thing being studied interacts with the other constituents of the system—a set of elements that interact to produce behavior—of which it is a part. This means that instead of isolating smaller and smaller parts of the system being studied, systems thinking works by expanding its view to take into account larger and larger numbers of interactions as an issue is being studied. This results in sometimes strikingly different conclusions than those generated by traditional forms of analysis, especially when what is being studied is dynamically complex or has a great deal of feedback from other sources, internal or external

Analyze complexityComplexity
Systems Thinking and Synthesis:
Synthesis is the opposite to analysis and defined in the same dictionary as follows:
1.Systematic combination of otherwise different elements to form a coherent whole.
2.Step in dialectic process where the affirmed concepts (the thesis) are countered with opposite affirmed concepts (the antithesis) to yield a final concept (the synthesis) that embraces or reconciles all acceptable concepts of the thesis and antithesis. This is how new (synthesized) knowledge emerges from the old knowledge.
3.Process in which substances combine to form completely new substances or duplicated natural products.
As shown in the figure complexity come from hierarchy of level, each level is more complex than the one below. In industrial synthesis, hydrocarbon molecules are combined in various combinations to numerous types of plastics and other new compounds. In natural synthesis, carbon dioxide and water are combined with sun's energy to produce glucose in plants (a process called photosynthesis).
At the end system models become part of the process specifications which are then used to for the system specifications. The character of systems thinking makes it extremely effective on the most difficult types of problems to solve: those involving complex issues, those that depend a great deal dependence on the past or on the actions of others, and those stemming from ineffective coordination among those involved. Examples of areas in which systems thinking has proven its value include:
Complex problems that involve helping many actors see the "big picture" and not just their part of it Recurring problems or those that have been made worse by past attempts to fix them Issues where an action affects (or is affected by) the environment surrounding the issue, either the natural environment or the competitive environment Problems whose solutions are not obvious
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