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The concept of relation schemas in relational database design. It covers the importance of designing easy-to-understand relation schemas, reducing redundant and null values, and avoiding spurious tuples. The document also introduces the concept of functional dependencies as a formal measure of relation schema goodness.
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Bottom
‐up
design
methodology
Top
‐down
design
methodology
Also
called
design
by
analysis
It^ starts
with
a^
number
of
groupings
of
attributes
into
relations
that
exist
together
naturally.
It^
involves
designing
the
relations
based
on
external
knowledge
derived
from
an
existing
implementation
of^
files
or
forms
or
reports.
The
relations
are
then
analyzed
individually
and
collectively,
leading
to
further
decomposition
until
all
desirable
properties
are
met.
Logical
or
conceptual
level
Implementation
or
storage
level
How
the
tuples
in
a^
relation
are
stored
and
updated.
This
level
applies
only
to
schemas
of
base
relations,
which
will
be
physically
stored
as
files.
Informal
measures
of
quality
for
relation
schema
design
are:
-^ Semantics
of
the
attributes
-^ Reducing
the
redundant
values
in
tuples
-^ Reducing
the
null
values
in
tuples
-^ Disallowing
the
possibility
of
generating
spurious
tuples
ENAME
EMPID
DOB
ADDRESS
DNUMBER
DNAME
DMGRID
a)
b) EMP_PROJ EMPID
PNUMBER
HOURS
ENAME
PNAME
PLOCATION
Mixing
attributes
of
multiple
entities
may
result
in
redundancy
of
data
in
the
database.
Redundant
information
in^
tuples
causes
two
problems:^ – Wastage
of
storage
space
-^ Problem
of
Update
anomalies
Wastage
of
storage
space…………….
PNUMBER
PNAME
PLOCATION
DNUM
ENMAE
EMPID
DOB
ADDRESS
DNUMBER
EMP_PROJ EMPID^ EMPLOYEEPROJECT
PNUMBER
HOURS
ENAME
PNAME
PLOCATION
WORKS_ON
EMPID
PNUMBER
HOURS
REDUNDANCY
REDUNDANCY
Insertion
anomalies
Deletion
anomalies
Modification
anomalies
Insertion
anomalies………………………
ENAME
EMPID
DOB
ADDRESS
DNUMBER
DNAME
DMGRID
EMP_DEPT
An
insertion
anomaly
.^ Until
the
new
faculty
member,
Dr.
Newsome,
is
assigned
to
teach
at
least
one
course,
his
details
cannot
be
recorded.