The document discusses normalization and different normal forms. It provides examples of relations that suffer from update anomalies due to redundant data and functional dependencies. The three normal forms discussed are: 1) First normal form (1NF) which disallows multi-valued and composite attributes. 2) Second normal form (2NF) which requires that non-key attributes are fully functionally dependent on the primary key. 3) Third normal form (3NF) which disallows transitive functional dependencies where one attribute determines another through an intermediate attribute.

1. Normalization
Lecture 2
Assistant Lecturer Huda A. Alameen
hudaa.alameen@uokufa.edu.iq

2. Redundant information in tuples and update
anomalies
 Information is stored redundantly
 Storage waste.
 Causes problems with update anomalies
•Insertion anomalies
•Deletion anomalies
•Update anomalies

3. Two relation schemas suffering from update
anomalies

4. Ename Ssn Bdate Adrress Dnumber Dname Dmgr_ssn
John 111 1/1/1990 A 5 R 33333
Smith 222 2/10/1988 B 5 R 33333
Zaid 112 5/8/1990 C 7 F 3335
NOOR 321 5/8/1990 Y 8 W 21333
Ali 342 2/11/1993 E 7 F 3335

5. Two relation schemas suffering from
update anomalies
• Insertion anomalies occur in PROJECT-EMPLOYEE relation because we can not insert
information about any new employee unless that employee is already assigned to a project.
Any attribute of the composite key (Proj-ID,Emp-ID) can not be NULL.
• Deletion anomalies occur when we delete the last tuple of a particular employee. In
this case, we not only delete the project information that connects that employee to a
particular project but also lose other information about the department for which this
employee works.

6. Two relation schemas suffering from
update anomalies
• Update anomalies occur because the department for which an employee works may
appear many times in the table. It is this redundancy of information that causes the
anomaly because if an employee moves to another department, we are now faced with
two problems: we either search the entire table looking for that employee and update
his Emp-Dpt value or we miss one or more tuples of that employee and end up with an
inconsistent state.

7. Normalization
 Normalization:
The process of decomposing unsatisfactory “bad” relations by breaking up their
attributes into smaller relations.
 Normal form:
Condition using keys and FDs of a relation to certify whether a relation schema is
in a normal form.

8. Functional Dependency

9. Example of FD constraints

10. Normal Forms
 First normal Form
 Second normal form
 Third normal form
 Boyce Codd Normal form
 Fourth normal form
 Fifth normal form

12. 1NF : First Normal Form
 Disallows
-Multivalued attributes
-Composite attributes

15. Normalization of nested relations into
1NF

16. 2NF : Second Normal Form
 Uses the concepts of FDs, primary key
 Definitions
Prime attribute: An attribute that is member of the primary key K
Full functional dependency: a FD Y -> Z where removal of any attribute from Y
means the FD does not hold any more
 Examples:
{SSN, PNUMBER} -> HOURS is a full FD since neither SSN -> HOURS nor PNUMBER
-> HOURS hold
{SSN, PNUMBER} -> ENAME is not a full FD (it is called a partial dependency )
since SSN -> ENAME also holds

17. 2NF : Second Normal Form
 A relation schema R is in second normal form (2NF) if every non-
prime attribute A in R is fully functionally dependent on the primary
key
 R can be decomposed into 2NF relations via the process of 2NF
normalization

18. 2NF : Second Normal Form

19. 3NF : Third Normal Form
 Disallows Transitive Dependency
 Definition:
Transitive functional dependency: a FD X -> Z that can be
derived from two FDs X -> Y and Y -> Z
 Examples:
SSN -> DMGRSSN is a transitive FD
Since SSN -> DNUMBER and DNUMBER -> DMGRSSN hold
SSN -> ENAME is non-transitive
Since there is no set of attributes X where SSN -> X
and X -> ENAME

20. 3NF : Third Normal Form