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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.
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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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cdac er diagram prsentation part-3

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 er model
Er diagram :-
These all wil be covered
Entity Sets
Relationship Sets
Mapping Constraints
Keys
E–R Diagram
Design of an E-R Database Schema
Reduction of an E-R Schema to Tables


Entity-Relationship Diagrams

Developed by Chen in 1965.
Purpose:
To facilitate database design by allowing the designer to express the logical properties of the database in an enterprise schema.

An enterprise schema is a description that corresponds to the conceptual level.

It is valid for any kind of DBMS and will remain correct even if the DBMS is changed.

The diagrams are basically design tools and documentation for the system.

Classified as a Semantic data model since it attempts to capture the meaning and structure.

Entity Relationship Model c

Representation of ER model

The items in the model represent the ‘things’ in the real-world, and the
relationships between the real-world things are expressed by relationships in the model.
The environment of the model consists of
Entities
Attributes
Keys
Super Keys, Candidate Keys, Primary Keys, Foreign Keys
Relationships
one-one , one-many, many-one, many - many
Dependencies
Existence Dependency
Aggregation and Generalization


Entity Sets

A database can be modeled as:
– a collection of entities,
– relationships among entities.

An entity is an object that exists and is distinguishable from other objects.
Example: specific person, company, event

An entity set is a set of entities of the same type that share same properties.
Example: set of all persons, companies, trees, holidays

Attributes

An entity is represented by a set of attributes, that is,
descriptive properties possessed by all members of an entity set.
Example:
customer = (customer-name, social-security,
customer-street, customer-city)
account = (account-number, balance)
Domain – the set of permitted values for each attribute
Attribute types:
– Simple and composite attributes.
– Single-valued and multi-valued attributes.
– Derived attributes.


Relationship Sets

A relationship is an association among several entities
An attribute can also be a property of a relationship set.

Degree of Relationship Set

Refers to number of entity sets that participate in a relationship set.

Relationship sets that involve two entity sets are binary sets.

Relationship sets may involve more than two entity sets. Relationship sets that involve two entity sets are ternary sets.

Roles

The labels “manager” and “worker” are called roles; they specify how employee entities interact via the works-for relationship set.

Roles are indicated in E-R diagrams by labeling the lines that connect diamonds to rectangles.

Mapping Cardinality
Express the number of entities to which another entity can be associated via a relationship set.

For a binary relationship set the mapping cardinality must be one of the following types:
– One to one
– One to many
– Many to one
– Many to many

Relationships
Relationships
Existence Dependencies
If the existence of entity x depends on the existence of entity y,
then x is said to be existence dependent on y.
– y is a dominant entity (loan)
– x is a subordinate entity (payment)

Keys
Each record in a table must be unique

A super key is a column, or a set of columns, that uniquely identifies a record in a table.

A minimal super key , with no proper subset that is also a super key, is called a candidate key.

A key consisting of more than one column is called a composite key.

A primary key is the candidate key that is selected by the database designer, to uniquely identify records within the table.
– the candidate keys not selected are called
alternate keys.

A foreign key is a column or set of columns within a table that is the candidate key of another table.

Weak Entity Sets
An entity set that does not have a primary key is referred to as a weak entity set.

The existence of a weak entity set depends on the existence of a strong entity set; it must relate to the strong set via a one-to-many relationship set.

The discriminator (or partial key) of a weak entity set is the set of attributes that distinguishes among all the entities of a weak entity set.

The primary key of a weak entity set is formed by the primary key of the strong entity set on which the weak entity set is existence dependent, plus the weak entity set’s discriminator.
Weak Entity Set
Specialization Example
Generalization
A bottom-up design process – combine a number of entity sets that share the same features into a higher-level entity set

Specialization and generalization are simple inversions of each other; they are represented in an E-R diagram in the same way.

Attribute Inheritance – a lower-level entity set inherits all the attributes and relationship participation of the higher-level entity set to which it is linked.

Aggregation
It is an abstraction of that allows us to group together objects into higher level objects.

Its inverse is decomposition, means breaking
up an object into its detailed components.
In ERD, aggregation is represented by placing a large labeled rectangle around the objects being aggregated, whether they are entity sets alone or include relationships.
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