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Title: Normalization of Database Tables


1
Normalization of Database Tables
  • CHAPTER 4

2
Chapter Objectives
  • Understand concepts of normalization
  • Learn how to normalize tables
  • Understand normalization and database design
    issues

3
Database Tables and Normalization
  • Normalization is a process for assigning
    attributes to entities.
  • It reduces data redundancies.
  • An un-normalized relation (table) stores
    redundant data, which can cause insertion,
    deletion, and modification anomalies.
  • In simple words Normalization means keeping a
    single copy of data in your database.
  • Normalization theory provides a step by step
    method to remove redundant data and undesirable
    table structures.

4
Normal Forms
  • Tables are normalized by applying rules to create
    a series of normal forms
  • First normal form (1NF)
  • Second normal form (2NF)
  • Third normal form (3NF)
  • Boyce/Codd normal form (BCNF)
  • Fourth normal form (4NF)
  • Projection Join normal form (PJNF, aka 5NF)
  • A table or relation in a higher level normal form
    always confirms to lower level normal forms.

5
Normal Forms
  • While higher level normal forms are available,
    normalization up to BCNF is often found to be
    adequate for business data.

6
First Normal Form
  • A relation is in 1NF if all underlying domains
    contain atomic values only, i.e., the
    intersection of each row and column contains one
    and only one value.
  • The relation must not contain repeating groups.

PNo PName ENo EName Jcode ChgHr Hrs
1 Alpha 101 John Doe NE 65 20 105 Jane Vo
SA 80 15 110 Bob Lund CP 60 40
2 Beta 101 John Doe NE 65 20 108 Jeb Lee
NE 65 15 106 Sara Lee SA 80 20
3 Omega 102 Beth Reed PM 125 20 105 Jane Vo
SA 80 10 Is the above relation in 1NF?
7
First Normal Form
  • The previous relation can be converted into first
    normal form by adding Pno and Pname to each row.

PNo PName ENo EName Jcode ChgHr Hrs 1 Alpha 101
John Doe NE 65 20 1 Alpha 105 Jane Vo
SA 80 15 1 Alpha 110 Bob Lund
CP 60 40 2 Beta 101 John Doe NE 65 20 2 Beta
108 Jeb Lee NE 65 15 2 Beta 106 Sara Lee
SA 80 20 3 Omega 102 Beth Reed
PM 125 20 3 Omega 105 Jane Vo SA 80 10
What is the primary key in this relation?
Do you see redundant data in this table? What
anomalies could be caused?
8
Functional Dependency Revisited
  • If A and B are attributes (or group of
    attributes) of a relation R, B is functionally
    dependent on A (denoted A B), if each value of
    A in R is associated with exactly one value of B
    in R.
  • A is called a determinant.
  • Consider the relation
  • Student (ID, Name, Soc Sec Nbr, Major, Deptmt)
  • Assume a department offers several majors, e.g.
    INSY department offers, INSY, MASI, and POMA
    majors.
  • How many determinants can you identify in Student?

9
Functional Dependency Revisited
  • A Dependency diagram

Name
Soc_Sec_Nbr
Major
Dept
10
Functional Dependency Revisited
  • Full functional dependency
  • Attribute B is fully functionally dependent on
    attribute A if it is functionally dependent on A
    and not functionally dependent on any proper
    subset of A.
  • This becomes an issue only with composite keys.
  • Transitive dependency
  • A, B and C are attributes of a relation such that
    A B and B C, then C is transitively
    dependent on A via B (provided that A is not
    functionally dependent on B or C)

11
Second Normal Form
  • Dependency diagram for Project

PNo
PName
ENo
ChgHr
Hrs
EName
JCode
12
Second Normal Form
  • A relation is in 2NF if
  • It is in 1NF and
  • every nonkey attribute is fully dependent on the
    primary key, i.e., no partial dependency.
  • A nonkey attribute is one that is not a primary
    key or part of a primary key.
  • We create new relations that are in 2NF through
    projection of the original relation.
  • Project(PNo, PName)
  • Employee(ENo, EName, Jcode, ChgHr)
  • Charge(PNo, ENo, Hrs)

13
2NF
  • 2NF

PNo
PName
ENo
ChgHr
EName
JCode
PNo
ENo
Hrs
14
Second Normal Form
  • Tables in 2NF

15
Second Normal Form
  • Note that the original relation can be recreated
    through natural join of the new relation.
  • Thus, no information is lost in the process of
    creating 2NF relations from a 1NF relation. This
    is called nonloss decomposition.
  • If a relation that is in 1NF has a non composite
    primary key (i.e., the primary key consists of a
    single attribute) what can you say about its
    status with regard to 2NF?
  • Do you see any redundant data in the tables that
    are in 2NF?
  • What anomalies could be caused by such redundancy?

16
Third Normal Form
  • A relation is in 3NF if
  • It is in 2NF and
  • every nonkey attribute is nontransitively
    dependent on the primary key (i.e., no transitive
    dependency).
  • Relation Employee has a transitive dependency
  • ENo JCode ChgHr
  • Employee can be replaced by two relations, that
    are in 3NF
  • Employee(ENo, EName, Jcode)
  • Job(JCode, ChgHr)


17
3NF
  • 3NF

PNo
PName
ENo
ChgHr
EName
JCode
JCode
PNo
ENo
Hrs
18
Third Normal Form
  • Tables in 3NF

19
Boyce-Codd Normal Form
  • A relation is in BCNF if
  • every determinant is a candidate key.
  • A determinant is an attribute (combination of
    attributes) on which some other attribute is
    fully functionally dependent.
  • BCNF is a special case of 3NF.
  • The potential to violate BCNF may occur in a
    relation that
  • contains two (or more) composite candidate keys,
  • these keys overlap and share at least one
    attribute.
  • Thus, if a table contains only one candidate key
    or only non-composite keys, then 3NF and BCNF are
    equivalent.

20
3NF Table Not in BCNF
  • Figure 4.7

21
Decomposition of Table Structure to Meet BCNF
Figure 4.8
22
Boyce-Codd Normal Form
  • Consider the following example
  • The members of a recruiting team interview
    candidates on a one-to-one basis. Each member is
    assigned a particular room on a given date. Each
    candidate is interviewed only once on a specific
    date. He/she may return for follow up interviews
    on later dates.
  • Interview (CID, IDate, ITime, StaffID, RmNo)

23
Boyce-Codd Normal Form
  • This relation has following functional
    dependencies
  • CID, IDate ITime, StaffID, RmNo
  • StaffID, IDate, ITime CID, RmNo
  • RmNo, Idate, Itime StaffID, CID
  • StaffID, IDate RmNo
  • This relation does not have any partial or
    transitive dependencies on the primary key (CID,
    IDate)
  • It is not in BCNF because (StaffID, Idate) is a
    determinant but not a candidate key.
  • The new relations in BCNF are
  • Interview (CID, IDate, ITime, StaffID)
  • Room(StaffID, IDate, RmNo)

24
Dependency Diagram
  • Dependency diagram

CID IDate ITime StaffID RmNo
Fig 1
CID IDate ITime StaffID RmNo
Fig 2
CID IDate ITime StaffID RmNo
Fig 3
25
Fourth Normal Form
  • A table is in 4NF if
  • it is in 3NF and
  • has no multiple sets of multivalued dependencies.
  • Consider the following example
  • Each course is taught by many teachers and
    requires many texts.

26
Fourth Normal Form
  • CTXN is in BCNF, because it is all key and there
    are no other functional dependencies.
  • It, however, has redundant data that could cause
    update anomalies.
  • This table shows two multivalued dependencies
  • Each course has a defined set of teachers and
  • Course Teacher
  • Each course has a defined set of textbooks.
  • Course Text
  • MVDs can exist only when the relation has at
    least three attributes.
  • An FD is a special case of MVD when the set of
    dependent values has a single value.

27
Fourth Normal Form
  • Tables in 4NF

CX Course Text Physics Basic Mechanics Physics Int
ro to Optics Math Modern Algebra Math Intro to
Calculus
28
Conversion to 4NF
Figure 4.15 Set of Tables in 4NF
Figure 4.14 Multivalued Dependencies
29
Normalization and Database Design
  • Normalization should be part of the design
    process
  • E-R Diagram provides macro view
  • Normalization provides micro view of entities
  • Focuses on characteristics of specific entities
  • May yield additional entities
  • Difficult to separate normalization from E-R
    diagramming
  • Business rules must be determined
  • Normalization purity is difficult to sustain due
    to conflict in
  • Design efficiency
  • Information requirements
  • Processing

30
Denormalization
  • Normalized (decomposed) tables require additional
    processing, thus reducing system speed.
  • Sometimes normalization is not done keeping in
    mind processing speed requirements and practical
    aspects of the situation.
  • A good example is storing Zip code and City as
    attributes in a Customer relation violates 3NF
    because City is transitively dependent on Cust ID
    via Zip Code.
  • Why should we not create a separate relation
    ZIP (ZipCode, City)?
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