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Saturday, April 24, 2010

cdac databse technology normaliztion part-4

Cdac original post part-3 for cdac mohali,cdac trivandrum,cdac pune,cdac hyderabad,noida and bangalore and recruitment from cdac.
Let me tell you before you go for this presenation how is the placement and recruitment in cdac going on.
I know about cdac hyderabad for cdac dabc its almost 100% and dac pune has around 80% ,desd pune has around 60% and desd hyderabad recruitment 70%.

Rest please you can enquire these things from orkut communities for 2010 created.
Here i am going on Data Normalization
Normalization

Database normalization is a technique for designing relational database tables to minimize duplication of information and to safeguard the database against certain types of logical or structural problems, namely data anomalies

Objectives

Data normalization aims to derive at records which avoid ?
Repetition of Data
Update anomalies
Insert Anomalies
Delete Anomalies


The Process of Normalization
Usually three steps (in industry) giving rise to
First Normal Form (1NF)
Second Normal Form (2NF)
Third Normal Form (3NF)
In academia
Boyce -Codd Normal Form (BCNF)
Fourth Normal Form (4NF)
Steps in Data Normalization
Attributes - Repeating Groups
When a group of attributes has multiple values then we say there is a repeating group of attributes in the entity

Functional Dependency


Consider a relation R that has two attributes A and B. The attribute B of the relation is functionally dependent on the attribute A if and only if for each value of A no more than one value of B is associated.
In other words, the value of attribute A uniquely determines the value of B

Stud_id -> stud_name
Stud_id -> Date of Birth
Module_id -> Module name
Marks -> grade

Full Functional Dependency

Let A and B be distinct collections of attributes from a relation R B is then fully functionally dependent on A if B is not functionally dependent on any subset of A.
(Stud_id, Module_id) -> marks

First Normal Form
A relation is in 1NF if and only if every attribute is single valued for
each tuple or row.

A relation is in 1NF if and only if there are no repeating groups of
Attribute values.


Example of First Normal Form
PURCHASE-ORDER (ORDER#, SUPPLIER#, ORDER-DATE
DELIVERY-DATE, (PART#, PART-DESCRIPTION,
QUANTITY-ORDERED, PRICE), TOTAL-PRICE)
Example in 1NF
PURCHASE-ORDER (ORDER#, SUPPLIER#, ORDER-DATE
DELIVERY-DATE, TOTAL-PRICE)
PURCHASE-ITEM-1 ( ORDER#, PART#, PART-DESCRIPTION,
QUANTITY-ORDERED, PRICE)
Example
STUDENT (Student#, student-name, student-address)

ENROLMENT (Student#, Course#, course-title,
tutor-name,tutor-staff#
1st Normal Form
Process results in separation of different objects
BUT anomalies may still exist
PURCHASE-ITEM-1( ORDER#, PART#, PART-DESCRIPTION,QUANTITY-ORDERED, PRICE)

PART-DESCRIPTION appears on every PURCHASE-ITEM occurrence.
This may result in anomalies when updating or deleting records
The problem in the example is that PART-DESCRIPTION is functionally dependent only on PART# (part of the identifier)
Second Normal Form
A relation is in 2NF if and only if it is in 1NF and all the
non-key attributes are fully functionally dependent on the
key.

Any entity type in 1NF is transformed to 2NF

Identify functional dependencies

Re-write entity types so that each non-identifying attribute is functionally dependent on the whole of the identifier
Example
PURCHASE-ORDER (ORDER#, SUPPLIER#, ORDER-DATE
DELIVERY-DATE, TOTAL-PRICE)
PURCHASE-ITEM-1 ( ORDER#, PART#, PART-DESCRIPTION,
QUANTITY-ORDERED, PRICE)
Functional Dependencies
PURCHASE-ORDER (ORDER#, SUPPLIER#, ORDER-DATE
DELIVERY-DATE, TOTAL-PRICE)
PURCHASE-ITEM-1 ( ORDER#, PART#, PART-DESCRIPTION,
QUANTITY-ORDERED, PRICE)

In 2nd Normal Form

Decompose PURCHASE-ITEM into two entity types
PURCHASE-ITEM (Order#, Part#, Quantity-Ordered, Price)
PART (Part#, Part-Description)
Original entity types are decomposed into three entity types in 2nd normal form
PURCHASE-ORDER (Order#,Supplier#, Order-Date, Delivery-Date, Total-Price)
PURCHASE-ITEM (Order#, Part#,Quantity-Ordered, Price)
PART (Part#, Part-Description)
Example in 2NF
STUDENT (Student#,Student-Name, Student-Address)
ENROLMENT ( Student#, Course#, Tutor-Name, Tutor-Staff#)
COURSE (Course#, Course-Title)

Third normal Form

A relation is in 3NF if and only if it is in 2NF and no
non-key attribute is transitively dependent on the key.


Any enity type in 2NF is transformed in 3NF

Determine functional dependencies between non identifying attributes
Decompose enity into new entities
Example
STUDENT (Student#,Student-Name, Student-Adderss)
ENROLMENT ( Student#, Course#, Tutor-Name, Tutor-Staff#)
COURSE (Course#,, Course-Title)
Functional Dependencies
STUDENT (Student#,Student-Name, Student-Adderss)
ENROLMENT ( Student#, Course#, Tutor-Name, Tutor-Staff#)
COURSE (Course#,, Course-Title)

Example in 3NF

STUDENT (Student#,Student-Name, Student-Adderss)
ENROLMENT ( Student#, Course#, Tutor-Staff#)
COURSE (Course#,, Course-Title)
TUTOR (Tutor-Staff#, Tutor-Name)
Example of Normal Forms

Functional Dependencies

Analysis of the sample FDs
1NF: Since PROGNAME and EMPID is the composite key, each cell contain single value so WORK is in 1NF.
The partial dependencies are
PROJNAME PROJMGR, BUDGET, STARTDATE
EMPID EMPNAME, SALARY, EMPMGR, EMPDEPT

Transform the relation work into an equivalent collection of 2NF relations
The relations schemes are:
PROJ ( PROJNAME, PROJMGR, BUDGET, STARTDATE)
EMP ( EMPID, EMPNAME, SALARY, EMPMGR, EMPDEPT)
WORK1 ( PROJANAME, EMPID, HOURS, RATING)
The above relations schemes are in 2NF.

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