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Analysis and Design
Decision tree is a tree like structure that represents the various conditions
and the subsequent possible actions. It also shows the priority in which the conditions
are to be tested or addressed. Each of its branches stands for any one of the
logical alternatives and because of the branch structure, it is known as a tree.
The decision sequence starts from the root of the tree that is usually on the
left of the diagram. The path to be followed to traverse the branches is decided
by the priority of the conditions and the respectable actions. A series of decisions
are taken, as the branches are traversed from left to right. The nodes are the
decision junctions. After each decision point there are next set of decisions
to be considered. Therefore at every node of the tree represented conditions are
considered to determine which condition prevails before moving further on the
This decision tree representation form is very beneficial to the analyst. The
first advantage is that by using this form the analyst is able to depict all the
given parameters in a logical format which enables the simplification of the whole
decision process as now there is a very remote chance of committing an error in
the decision process as all the options are clearly specified in one of the most
Secondly it also aids the analyst about those decisions, which can only be
taken when couple or more conditions should hold true together for there may be
a case where other conditions are relevant only if one basic condition holds true.
In our day-to-day life, many a times we come across complex cases where the
most appropriate action under several conditions is not apparent easily and for
such a case a decision tree is a great aid. Hence this representation is very
effective in describing the business problems involving more then one dimension
They also point out the required data, which surrounds the decision process.
All the data used in the decision making should be first described and defined
by the analyst so that the system can be designed to produce correct output data.
Consider for example the discount policy of a saree manufacturer for his customers.
According to the policy the saree manufacturer give discount to his customers
based on the type of customer and size of their order. For the individual, only
if the order size is 12 or more, the manufacturer gives a discount of 50% and
for less than 12 sarees the discount is 30%. Whereas in case of shopkeeper or
retailers, the discount policy is different. If the order is less than 12 then
there is 15% discount. For 13 to 48 sarees order, the discount is 30%, for 49
to 84 sarees 40% and for more than 85 sarees the discount is 50%. The decision
policy for discount percentage can be put in the form of a decision tree displayed
in the following figure.
The decision trees are not always the most appropriate and the best tool for
the decision making process. Representing a very complex system with this tool
may lead to a huge number of branches with a similar number of possible paths
For a complex problem, analyzing various situations is very difficult and can
confuse the analyst.
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