- 306 Views
- Updated On :
- Presentation posted in: General

Normalization Concepts. CIS 507 Database Programming. Introduction. Two types of Anomalies associated with databases. Modification Anomaly an unexpected consequence of changing the actual data in a database Design Anomaly a flaw in the logical design of the database itself

Related searches for Normalization Concepts

Download Presentation
## PowerPoint Slideshow about 'Normalization Concepts ' - issac

**An Image/Link below is provided (as is) to download presentation**

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

Introduction

- Two types of Anomalies associated with databases.
- Modification Anomaly
- an unexpected consequence of changing the actual data in a database

- Design Anomaly
- a flaw in the logical design of the database itself

- Basic Principles:
- For each modification anomaly there is a design anomaly
- For each design anomaly there are associated modification anomalies

EmployeeID

EmployeeID

111222

111222

EmployeeID

Types of modification anomalies:

- Insertion:
- add a new student—since the key is STUDENT-ID + COURSE, a student can only be added when the course has been completed.

- Deletion:
- of student 112233 results in the loss of information about course CIS 503.

- Update.
- Student 112244 to Tonya Marshall requires the change to take place in several places.

Normalization

- Design anomalies have been classified and criteria for removal of the anomalies have been developed.
- The process of removing design anomalies is called Normalization.
- A Normal Form is associated with the removal of a specific type of anomaly.
- The known normal forms from lowest to highest are: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF, DKNF
- Any design which is evaluated as a higher form automatically satisfies the lower forms.

Normalization

- Theory of Normalization Contributors
- Dr. E. F. Codd introduced the first three normal forms in the same paper in which the Relational Model was introduced ( A Relational Model of Data for Large Shared Databanks, CACM, Vol 13, No 6, June, 1970.)
- Dr. R. F. Boyce extended Codd's original three forms.
- Dr. R. Fagin extended the theory as proposed by Codd and introduced another way of evaluating a design.
- Dr. D. M. Kroenke has been instrumental in clarifying the theory of normal forms in his role as educator.

Known Normal Forms.

- The normal forms in order from lowest to highest are
- First Normal Form (1NF). Elimination of repeating field types
- Second Normal Form (2NF). Elimination of partial key dependencies.
- Third Normal Form (3NF). Elimination of transitive key dependencies among non-key attributes.
- Boyce-Codd Normal Form (BCNF). Elimination of partial key dependencies upon non-key attributes.
- Fourth Normal Form (4NF). Elimination of multi-valued dependencies.
- Fifth Normal Form (5NF). Elimination of join anomalies.
- Domain Key Normal Form. Elimination of all modification anomalies.

Basic Definitions.

- Assumptions:
- e is an entity type
- ε is the set of attributes for e
- A, B, C, ... are non-empty subsets of ε

Basic Definitions.

- Functional Dependence: B is Functionally Dependent on A if for each value of A there is exactly one value of B.
- A is said to Functionally Determine B
- A is called a Determinant.
- The relationship between A and B is represented as A --> B
- If A --> ε, A is said to be an Identifier for the entity type e

- Example
e = STUDENT-DORM-FEEε = {STUD-ID, STUD-NAME, DORM, DORM-FEE}A = {STUD-ID}B = {DORM}C = {DORM-FEE}A --> ε, B --> C

Key

- K is a Key for the entity e if and only if
- K --> ε and
- no non-empty subset of K determines ε.

- Example (From last example)
- A = {STUD-ID} is a key for e = STUDENT-DORM-FEE
- {STUD-ID, DORM-FEE} is not a key for e.

- An attribute which belongs to the selected key A is called a Key Attribute; all other attributes are called Non-Key Attributes.

First Normal Form (1NF) (Repeating Attribute Types)

- A is a repeating attribute type or repeating field type if for each occurrence of e there may be 0, 1, or more occurrences of values for A.
- The data structure used for a repeating attribute types gives rise to maintenance difficulties.
- Static approach: embedding repeating field type is within the entity type (implemented as an array)
- allocation for maximal perceived use results in unused space or
- insufficient storage for some entities if the maximal perceived use is underestimated

- Dynamic approach: data structure which requires more complex functions for management.

- Static approach: embedding repeating field type is within the entity type (implemented as an array)
- Example.
- e = {STUD-ID, STUD-NAME, COURSE, COURSE-GRADE}COURSE and COURSE-GRADE form a repeating type pair of attributes since any student will have completed 0, 1, or more courses.

First Normal Form (1NF) (Atomic Attributes)

- An attribute is Atomic if the attribute defines the lowest level of usage of data collected for the attribute.
- Example.e = {STUD-ID, STUD-NAME, COURSE, COURSE-GRADE}
- No guarantee that LAST-NAME will available since the design does not define it as an attribute.
- Examples for Johnson Albert Gilbert:JOHNSON GILBERT, GILBERT JOHNSON, J. A. GILBERT, J. GILBERT, GILBERT J., GILBERT J. A., JOHNSON A. GILBERT, J. ALBERT GILBERT, GILBERT JOHNSON A., GILBERT JOHNSON ALBERT,JOHNSON ALBERT GILBERT, GILBERT J. ALBERT, etc.
- The forms shown above might all be present for different entities in the data collection.
- Any algorithm designed to extract the desired information would have to consider all possibilities.
- Avoided by properly identifying the lowest level of use during the design phase rather than relying on an application to obtain the desired data.

First Normal Form (1NF) (Definition)

- An entity type e is in FIRST NORMAL FORM (1NF) if and only if
- e has no repeating attribute types AND
- all attribute types of e are atomic.

Symbolic Table.

Insertion Anomaly.b.Deletion Anomaly.c.Update Anomaly.

Second Normal Form (Partial Key Dependency)

An entity type e with key, K, has a Partial Key Dependency if and only if a collection of non-key attributes is determined by (or functionally dependent on) a non-empty proper subset of K.

Second Normal Form (Definition)

An entity type e is in SECOND NORMAL FORM (2NF) if and only if a.e is in 1NF ANDb.e has no partial key dependencies.

Symbolic Table.

- Insertion Anomaly.
- Deletion Anomaly.
- Update Anomaly.

Third Normal Form (3NF).

For A and C, attribute collections for an entity type e, there is a Transitive Dependency of C upon A if there is an attribute collection, B, of e for whicha.A --> B andb.B --> C.

Third Normal Form (Definition)

An entity type e is in THIRD NORMAL FORM (3NF) if and only if a.e is in 2NF ANDb.e has no transitive dependencies of one non-key attribute collection upon another non-key attribute collection

Example

Difficulties.

Symbolic Table.

Insertion Anomaly.Deletion Anomaly.Update Anomaly.

Boyce-Codd Normal Form (BCNF).

Attribute collections A and B of an entity type e are Candidate Keys for e if and only ifa.A is a key for e andb.B is a key for e andc.A is not equal to B.

Boyce-Codd Normal Form (BCNF) (Definition)

An entity type e is in BOYCE-CODD NORMAL FORM (BCNF) if and only if a.e is in 3NF ANDb.all determinants of e are candidate keys.

Example.

Difficulties.

Token Diagram (Abstraction) Second Normal Form (Partial Key Dependency)

Symbolic Table.

a.Insertion Anomaly.b.Deletion Anomaly.c.Update Anomaly.