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2.1.3.2 Normalization
“There are 3 steps in order to make a good data model such as: “[4]
1. A good data model is simple. As a general rule, the data attributes that describe an
entity should describe only that entity.
2. A
good data
model
is
essentially
nonredundant.
This
means that each data
attribute, other that foreign keys, describes at most one entity.
3. A
good data
model should be
flexible and adaptable to
future
needs.
This
means
data
model
must
not
fulfill
today’s
business
requirements, but also fulfill future
business
needs’.
In order to make those criteria above, we need to do techniques commonly used by
system analyst which
is called normalization. Normalization, according to quotation from
Whitten
[4],
is a data analysis
techniq ue
that organizes data attributes such that they are
grouped to form nonredundant, stable, flexible, and adaptive entities. Furthermore,
Whitten
[4]
said
that
there
are
3
steps
techniques
that
place
the
data
model
into
first
normal
form, second
normal
form, and third normal
form.
1. An entity
is
in first
normal
form
(1NF)
if
there
are
no
attributes
that
can
have
more
than
one
value
for
a
single
instance
of
the
entity.
Any
attributes
that
can
have
multiple
values
actually
describe
a
separate
entity,
possibly
an
entity
and
relationship.
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