Database Fundamentals Presentation

8/6/2019 Database Fundamentals Presentation

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14/01/2009 Lord's Kitchen 1

Database FundamentalsDatabase FundamentalsBasic & Intermediate


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Icons usedIcons used

Questions References

Key Concepts

A Welcome Break

Demo

Brain Teasers


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Module InformationModule InformationModule

Description

This module provides students with the basic knowledge

and skills that are needed to understand the need fordatabases and how they can design them

Level Basic & Intermediate

Prerequisites Basic knowledge of data and files


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Module Objective & OutlineModule Objective & Outline

Module Objective:After completing this Module, you should :

Understand what is a Database System

Explain briefly different types of Database Systems

Be able to create a Database environment with ER Modeling

Have a broad overview on Relational Database Management System

Have an introduction to Structured Query Language

Understand how the DBMS & its host computer system intercommunicate

Be aware of the new trends in Database


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Module OutlineModule Outline

Module Flow:

4.Structured

QueryLanguage

2.Types of

DatabaseSystems

3.Creating a

DatabaseEnvironment

5.Internal

Management

1.What is aDatabase

System

6.Database

Trends


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1.0 Database System1.0 Database System

Learning Objective: At the end of this Topic you will be able to

Understand what is a Database System

Know how files are organized

Appreciate the advantages of using a DBMS

over a traditional file system

Be aware of the Database Architecture


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What is a Database SystemWhat is a Database System

A Database System is essentially a computerizedrecord-keeping system.

A database-management system (DBMS) consists of

a collection of interrelated data and a set ofprograms to access those data.

Database systems are designed to manage large

volume of information


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File Organization : Terms and ConceptsFile Organization : Terms and Concepts

Database: Group of related files

File: Group of records of same type

Record: Group of related fields

Field: Group of words or a completenumber

Byte: Group of bits that represents asingle character

Bit: Smallest unit of data; binarydigit (0,1)

Data Hierarchy in a Computer System


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Entity: Person, place, thing, event about which information ismaintained

Attribute: Description of a particular entity

Key Field: Identifier field used to retrieve, update, sort a record


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Data redundancy

Program-Data dependence

Lack of flexibility

Poor security

Lack of data-sharing andavailability

No concurrency control

Problems with the Traditional File Environment

Traditional File Processing


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DBMS and its AdvantagesDBMS and its AdvantagesvA Database Management System is a collection of programs that

enables users to create and maintain a database. It is ageneral purpose software system that facilitates processes ofdefining, constructing and manipulating databases for variousapplications.

vAdvantages of Database approach: Controlling Redundancy

Restricting Unauthorized access

Providing persistent storage for program objects and data structures

Permitting inference and actions using deduction rules

Providing multiple user interface

Representing complex relationships among data Enforcing integrity constraints

Providing backup and recovery


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Database Management System (DBMS)Database Management System (DBMS)


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DBMS ArchitectureDBMS Architecture


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Data Independence Logical data independence : capacity to

change conceptual schema without

having to change external schema.

Physical data independence : capacity to

change internal schema without changing

conceptual schema.

DBMS ArchitectureDBMS Architecture


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Functions of DBMSFunctions of DBMS Data definition :

Specifies contentand structure of database and defines each data

element

Data manipulation :

Manipulates data in a database

Data security and integrity : Monitors user requests and rejects any unauthorized attempts

Data recovery and concurrency :

Enforces certain controls for recovery and concurrency

Data dictionary:

Stores definitions of data elements, and data characteristics

Performance :

Functions should be performed efficiently


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Requirements of a DBMSRequirements of a DBMS


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Database System : RecapDatabase System : RecapWhy do businesses have trouble finding the information

they need in their information systems?

How does a database management system help businesses

improve the organization of their information?

What are the advantages of using a DBMS over a

traditional file system

State the major functions and requirements of a DBMS


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QuizQuizIf a Customer Database has the following fields:

EmpId, EmpName, Salary and DeptName, Whatwould be the ideal Key field and why ? EmpID

EmpName

DeptName

EmpId+DeptName


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2.0 Types of Databases2.0 Types of Databases

Learning Objective: At the end of this Topic you will be able to

Explain briefly the various types of Database

Systems

Relational DBMSHierarchical DBMS

Network DBMS

Object-Oriented Databases


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Relational Database ModelRelational Database ModelRepresents data as two-dimensional tables called relations

Relates data across tables based on common data element Examples: DB2, Oracle, MS SQL Server


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Three Basic Operations in aThree Basic Operations in aRelational DatabaseRelational Database


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Three Basic Operations in aThree Basic Operations in aRelational DatabaseRelational Database

SELECT

PROJECT

JOIN


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Hierarchical Database ModelHierarchical Database ModelIt is a pointer based modelOrganizes data in a tree-like structureStores data in tables and views relationships as linksSupports one-to-many parent-child relationshipsPrevalent in large legacy systems


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Network DBMSNetwork DBMS

Depicts data logically as many-to-manyrelationshipsOrganizes data in tables and views relationships

as links

It is also a pointer based modelOrganizes data in arbitrary graphs


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Hierarchical and Network DBMSHierarchical and Network DBMS

Some of the Disadvantages Outdated

Complex pointer based organization

Less flexible compared to RDBMS

Lack support for ad-hoc and English language-like queries


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Object-Oriented DatabasesObject-Oriented Databases

Object-oriented DBMS: Stores data and

procedures as objects that can be retrieved

and shared automatically

Object-relational DBMS: Provides capabilities of

both object-oriented and relational DBMS


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Types of DatabasesTypes of Databases :: SummarySummary

In a relational database the data is perceivedas tables (and nothing but tables) by the

user

The relational operators available are used to

manipulate the data in the tables


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3.0 Creating a DB environment3.0 Creating a DB environment

Learning Objective:

At the end of this Topic you will

Have the ability to model an application systembased on the E-R Modeling approach.

Understand the Relational Database concepts likeNormalization, Data Integrity, Relational

Operations like Union, Intersection etc.

Be able to Design Relational Databases based on

E-R Models or System Requirements for an

application.


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Introduction to Data ModelingIntroduction to Data ModelingWhat is Data Modeling?

A technique for analyzing requirements and for

identifying the information needs of an organization

Why Data Modeling is important?

Cannot build a good system without knowing

what data needs to be captured and how it needs to

be organized


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Introduction to Data ModelingIntroduction to Data ModelingAn Overview :

Conceptual representation of the data structures required by adatabase

Data structures include the data objects, the associations betweendata objects, and the rules which govern operations on theobjects

Focuses on what data is required and how it should be organized Independent of hardware or software constraints

Data Model And Database Design:

Data Model is to a Database what a Building plan or a blueprint isto a Building

A Database Design translates a data model into a database

A Data Model is the conceptual design of a database


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E-R ModelingE-R Modeling

Originally proposed by Peter Chen (1976)Views the real world as entities and relationshipsKey component is the E-R DiagramMost common model used for designing relational databases

Entity- An identifiable object or concept of

significance

Attribute- Property of an entity or relationship

Relationship- An association between entities

Identifier- one or more attributes identifying aninstance

(occurrence) of an entity


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Entity relationship diagramEntity relationship diagram


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hasworksforDept No.

Name

NameEmp Id.

Entity

Relations

hip

Attributes

EMPLOYEEDEPARTMENT

Identifier


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Entity

Any object or thing of significance about which data

needs to be collected and maintained

Could be

Concrete or tangible like a person or a building

Abstract like a concept or activity

Analogous to a table in a relational database

Examples: EMPLOYEES, PROJECTS, INVOICES



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Entity Rules

Any thing or object may only be represented by one entity. Entities are

mutually exclusive in all cases.

Each entity must be uniquely identifiable. Each instance (occurrence) of

an entity must be separate and distinctly identifiable from all other

instances of that type of entity.

Entity Classification and Types

Classified as dependent and independent

An independententity is one that does not rely on another for

identification

A dependent entity is one that relies on another for identification

In some, methodologies, the terms used are strong and weak,

respectively



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Entity Classification and Types

Fundamental entity - An entity that exists and is of interest in its

own right. Generally, most entities in the data model are

fundamental entities.

Example :Department and Employee are both fundamental entities

Special Entity Types

Associative Entity -Used to associate two entities in order to reconcile a

many-many relationship

Sub-type/super-type- Used in generalization hierarchies to

represent a subset of instances of their of parent entity



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Generalization Hierarchies

Generalization occurs when two or more entitiesrepresent categories of the same real-world object.

Example: CAR and TRUCK represent categories of the

same entity, VEHICLE is the super-type; CAR and TRUCK

would be the subtypes



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Form of abstraction that specifies that two or more entities that

share common attributes can be generalized into a higher level

entity type called a super-type or generic entity.

The lower-level of entities become the sub-type, or categories,

to the super-type. Sub-types are dependent entities.



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Sub-types can be either mutually exclusive (disjoint) oroverlapping (inclusive)

In an overlapping hierarchy an entity instance can be part of

multiple subtypes

Example: Entity PERSON represents people at a university. It has three subtypes,

FACULTY, STAFF, and STUDENT. A STAFF member could also be registered as a

STUDENT

PERSON

FACULTYSTUDENT STAFF



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Generalization Hierarchies - NestedGeneralization Hierarchies - Nested

PERSON

FACULTYSTUDENT

UNDERGRAD GRADUATE



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AttributeAttributes describe a property or a characteristic of an

entity

A particular instance of an attribute is a value.

For example John Doe is one value of the attribute Name.Simple attributeContains only atomic values

Composite attributeHas component attributes

StudentName

FName

LName

MI

DOB

Simple Composite



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Attribute Classification

Single-valued attribute

Has exactly one value per instance of an entity

Multi-valued attribute

Contains repeating values per instance of an entity

v

Module

Student

Math

Physics

Id

Multi-valued

Single-

valued



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Relationship

Represents an association between two or more

entities

Examples

- Employees work for Departments

- Departments manage one or more projects

- Employees are assigned to projects

- Projects have sub-tasks

- Orders have line items

Defined in terms of:

- Degree

- Connectivity- Cardinality

- Direction

- Type

- Existence



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Degree

Number of entities associated with the relationshipBinary relationships, the association between two entities is the

most common type in the real world. N-ary is the general form for

degree n

Connectivity

Mapping of associated entity instances in the relationship.The values of connectivity are "one" or "many.

Cardinality

Actual number of related occurrences for each of the two entities.

The basic types of connectivity for relations are: one-to-one, one-to-many,

and many-to-many.



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Connectivity and Cardinality

A one-to-one (1:1) relationship is when at most one instance of a entity A

Is associated with one instance of entity B.

For example:

Employees in the company are each assigned their own office. For each

Employee there exists a unique office and for each office there exists a

unique employee.

A one-to-many (1:N) relationships is when for one instance of entity A,

there are zero, one, or many instances of entity B, but for one instance

of entity B, there is only one instance of entity A.

An example :

A department has many employees each employee is assigned to one department



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Connectivity and Cardinality

A many-to-many relationship, is when for one instance of entity

A, there are zero, one, or many instances of entity B and for

one instance of entity B there are zero, one, or many instances

of entity A.

An example is:employees can be assigned to no more than two projects at the

same time; Project must have assigned at least three employees



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Direction

Indicates the originating entity of a binary relationship. The entity

from which a relationship originates is the parent entity; the entity

where the relationship terminates is the child entity.

Type

The direction of a relationship is determined by its connectivity.

Identifying and Non-identifying

An identifying relationship is one in which one of the child entities is also

dependent entity.

A non-identifying relationship is one in which both entities are

independent.



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ExistenceDenotes whether the existence of an entity instance is

dependent

upon the existence of another, related, entity instance.

Defined as either mandatory or optional.

Mandatory and optional relationship

If an instance of an entity must always occur for an entity to beincluded in a

relationship, then it is mandatory. If the instance of the entity is

not required, it

is optional.

Example: Mandatory :Every project must be managed by a

single department Optional : Employees may be assigned to work on

projects


d l


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E-R Notation

No standard notation

Original notation by Chen

Common notations are: Bachman, crow's foot, and IDEFIX

All styles represent entities as rectangular boxes and

relationships as lines connecting boxes

Each style uses a special set of symbols to represent the

cardinality of a connection


d li


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Entities

Represented by labeled rectanglesThe label is the name of the entity

Entity names should be singular nouns.

Relationships

Represented by a solid line connecting

two entities.Name written above the line

Relationship names should be verbs

Employee

Department

Works for


E R M d li


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Attributes

Listed inside the entity rectangle

Underlined

Names should be singular nouns

Cardinality

Many is represented by a line ending in a crow's

foot. If omitted, cardinality is one

Existence

Represented by placing a circle or a

perpendicular bar on the line

Mandatory existence is shown by the bar next to

the entity for an instance that is required

Optional existence is shown by placing a circle

next to the entity that is optional

EmployeeEmpID

EmpName


d lE R M d li A i


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How to create an E-R Model from Requirements ?Step 1: Identify Entities

Entities are things people talk about, record information about

and do work on by definition

Any keyword (noun) is a candidate

Identify generic object from reference to instances or

occurrences

Combine synonyms to represent a single entity

An Example : Purchase Order - System Requirements

A buyer creates a purchase order (PO) as and when the need arises. A PO is for a Specific vendor. A PO has one or more line items. A buyer cannot create a PO of

Total value more than his approval limit. A PO can be sent to the vendor by mail,

fax, EDI. A PO can be canceled before it is submitted. A PO can be linked to a

sales order

E-R Modeling - AssignmentE-R Modeling - Assignment

R d liE R M d li


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Step 1: Identify EntitiesEntities

Purchase Order (PO) Buyer? Vendor Line Items Sales Order

Approval Limit?Buyercharacterizes a PO Approval Limit characterizes a Buyer

What does it tell us?

Approval Limit is not an entityBuyer is an entity

Approval Limit is an attribute of the entity Buyer



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E R M d liE R M d li


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Step 2: Identify Relationships

Grid Technique

PO

PO replaced by Buyer

Buyer creates a is approver of

Vendor

Vendor suppliesagainst a

- - Line

Line belongs to a - created for

item suppliedby

-



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Step 3 : Identify Attributes

An attribute is any detail that server to identify, classify, quantify or

express the the state of an entity

Ask the following question for each entity What information do you

need to know or hold about ?

Potential attributes are easily found by examining paper forms




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Step 3: Identify Attributes

Purchase Order No __________Buyer _________ Vendor ___________Date Created ______

No Item Quantity Value ___ ___________ ________________ ___ ___________ ________________

___ ___________ ________________

Shipping AddressStreet _________City __________Zip _______ Total Value ______

Example Purchase Order Form

Purchase Order NoVendor Buyer Date Created

Item? Address City State Zip Total Value?




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E-R Model of the Purchase Order Example

PURCHASEORDER

VENDOR

BUYER

creates

created by

supplies against

created for a

LINE

has

belongs to

ITEM

created for

exists on


E R M d liE R M d li g


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Major Modeling TechniquesPeter Chens original entity/relationship

diagramsInformation EngineeringRichard Barkers notation, used by Oracle

corporationIDEF1XObject Role ModelingUnified Modeling Language (UML)Extensible Markup Language (XML)


E R M d liE R M d li g


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Major Modeling TechniquesData Modeling has sets of two audiences:

User community - Uses the models to verify that the analysts

understand their environment and their requirements.

Systems designers - Use the business rules implied by the

models as the basis for their design of computer systems.

Different techniques are better for one audience or the

other.

All techniques are fundamentally the same

Differences are mainly in syntactic or notational


R l ti l M d lRelational Model


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Relational ModelRelational Model

Objective :

To give an informal introduction to relational

concepts especially as they

relate to relational database design issues.

What it is not ? This does not give a complete description of relational

theory.

R l ti l M d lRelational Model


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Formally introduced by Dr. E. F. Codd in 1970

Represents data in the form of two-dimension

tables

A relational database is a collection of two-dimensional tables

Basic understanding of the model needed to

design and use relational databases




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Tables, Columns and RowsRelationships and KeysData IntegrityNormalizationWhat is a table?

Represents some real-world person, place, thing, orevent

Two-dimensional Columns Rows

Cou rs e No . Co ur s e _Title C_Hr s .De pt. C

CIS 120 Intro to CIS 4 Cis

M KT 333 Intro to M k ting 3 M KTECO 473 Labor Econ. 3 ECO

BA201 Intro to Stat. 5 ECO

n r o o as e




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TableColumns represent a property of the person, place,thing or event that the table represents

Rows represent an occurrence or instance of what thetable represents

A data value is stored in the intersection of a row and

columnEach named column has a domain, which is the set of

values that may appear in that column

Empid Name Level DOJ Manager

101412 John M3 4/10/98 101667

102235 Nancy M4 1/23/01 101412

101398 Mike S1 8/15/95 101667

101667 Jeff M2 6/2/96 100351

103893 Cindy M3 7/17/95 101284

101116 Rahul S2 2/20/00 101412102739 Scott C1 4/13/01 101667

Employee



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In this document Formal Terms Many Database Manuals

Table Relation Table

Column Attribute Field

Row Tuple Record

Table - Terminology



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Salient features of a relational table

Values are atomic (1NF) Column values are of the same kind (Domain)

Each Row is unique (Primary Key)

Sequence of columns is insignificant

Sequence of rows is insignificant

Each column must have a unique name

Relationships and Keys

Keys - Fundamental to the concept of relational databases

Relationship - An association between two or more tables

defined by means of keys



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Primary Key

Column or a set of columns that uniquely identify a row in a

table

Must be unique and must have a value

Foreign Key

Column or set of columns which references the primary key or

a unique key of another table

Rows in two tables are linked by matching the values of the

foreign key in one table with the values of the primary key in

another

EMP_ID in table EMPLOYEE is the primary key

DEPT_NO in table DEPARTMENT is the primary key

DEPT_NO in table EMPLOYEE is a foreign key

Examples



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Data Integrity

Ensures correct and consistent navigation and manipulation ofrelational tables

Two types of integrity rules

Entity integrity

Referential integrity

The entity integrity rule states that the value of the primary key

can never be a null value

The referential integrity rule states that if a relational table has a

foreign key, then every value of the foreign key must either be null or

match the values in the relational table in which that foreign key is a

primary key



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Data Manipulation

Relational tables are equivalent to sets Operations that can be performed on sets can be

performed on relational tables

Relational Operations such as :

Selection Projection Join

Union

Intersection

Difference

Product

Division

UNION

INTERSECTION

DIFFERENCE



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Selection

The select operator, sometimes called restrict to preventconfusion with the SQL SELECT command, retrieves subsets of rows

from a relational table based on a value(s) in a column or columns

A B C D E1 A 212 Y 2

2 C 45 N 84

3 B 8656 N 4

4 D 324 N 56

5 C 5656 Y 34

6 A 445 N 4

7 B 546 Y 55



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Projection

The project operator retrieves subsets of columns from a relationaltable removing duplicate rows from the result

A B C D E

1 A 212 Y 2

2 C 45 N 84

3 B 8656 N 4

4 D 324 N 56

5 C 5656 Y 34

6 A 445 N 4

7 B 546 Y 55



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k x y1 A 2

2 B 4

3 C 6

k x y

1 A 2

4 D 8

5 E 10

Table A

Table B

A TIMES B

ak ax ay bk bx by

1 A 2 1 A 2

1 A 2 4 D 8

1 A 2 5 E 10

2 B 4 1 A 2

2 B 4 4 D 8

2 B 4 5 E 10

3 C 6 1 A 2

3 C 6 4 D 8

3 C 6 5 E 10

Product

The product of two relational tables, also called the Cartesian Product, isthe concatenation of every row in one table with every row in the second.

The product of table A (having m rows) and table B (having n rows) is the

table C (having m x n rows). The product is denoted as A X B or A TIMES B



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Join

Combines the product, selection and projection operationsCombines (concatenates) data from one row of a table with rows from

another or same tableCriteria involve a relationship among the columns in the join relational table

If the join criterion is based on equality of column value, the result is called an equi join

A natural join is an equi join with redundant columns removedJoins can also be done on criteria other than equality. Such joins are called non-equi joins

k a b

1 A 2

2 B 43 C 6 k c

1 aa

3 bb

5 cc

k a b k c1 A 2 1 aa

3 C 6 3 bb

k a b c1 A 2 aa3 C 6 bb

Table A

Equi-JoinTable B

Natural Join



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Union

The UNION operation of two tables is formed by appending rows fromone table to those of a second to produce a third. Duplicate rows are

eliminated

Tables in an UNION operation must have the same number of columns

and corresponding columns must come from the same domain

Table A

Table B

k x y

1 A 2

2 B 4

3 C 6

k x y1 A 2

4 D 8

5 E 10

k x y

1 A 2

2 B 4

3 C 6

4 D 8

5 E 10

A Union B



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The UNION operation of two tables is formed by appending rows from one table to

those of a second to produce a third. Duplicate rows are eliminatedTables in an UNION operation must have the same number of columns and

corresponding columns must come from the same domain

Table A

Table B

k x y

1 A 2

2 B 4

3 C 6

k x y1 A 2

4 D 8

5 E 10

k x y

1 A 2

2 B 4

3 C 6

4 D 8

5 E 10

A Union B



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Intersection

The intersection of two relational tables is a third table thatcontains common rows. Both tables must be union compatible. The

notation for the intersection of A and B is A [intersection] B = C or A

INTERSECT B

k x y

1 A 2

2 B 4

3 C 6

k x y

1 A 2

4 D 8

5 E 10

k x y

1 A 2

Table A

Table B

A Intersect B



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Difference

The difference of two relational tables is a third that contains thoserows that occur in the first table but not in the second. The Difference

operation requires that the tables be union compatible.

The notation for difference is A MINUS B or A-B. As with arithmetic, the order of

subtraction matters. That is, A - B is not the same as B - A.

k x y

1 A 2

2 B 4

3 C 6Table A

Table B

A MINUS B

k x y

1 A 2

4 D 8

5 E 10

B MINUS A

k x y

2 B 4

3 C 6

k x y

4 D 8

5 E 10



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Table A Table B

A DIV B

Division

The division operator results in columns values in one table forwhich there are other matching column values corresponding to every

row in another table.

k x y

1 A 2

1 B 4

2 A 2

3 B 4

4 B 43 A 2

x y

A 2

B 4

k

1

3

NormalizationNormalization


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Normalization theory is based on the concepts of normal forms. A

relational table is said to be a particular normal form if it satisfieda certain set of constraints.

We shall discuss four normal forms in this Module.

The concept offunctional dependencyis the basis for the first three normal forms.

A column Y of a relational table is said to be functionally dependentupon column X

when values of column Y are uniquely identified by values of column X.

What is Functional Dependency ?

Full functional dependence applies to tables with composite keys. Column Y in relational

table R is fully functional on X of R where X is a composite key if it is functionally

dependent on X and not functionally dependent upon any subset of X.



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NormalizationNormalizationUn normalized

Relation

NormalizedRelation (1NF)

2 NF

3 NF

Boyce/Codd NF

Removerepeating groups

Remove partialdependencies

Remove transitivedependencies

Remove remainingAnomalies resultingfrom FDs

Remove multivalueddependencies



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An Example : A company obtains parts from a number of suppliers. Each

supplier is located in one city. A city can have more than one supplier located

there and each city has a status code associated with it. Each supplier may

provide many parts.

The company creates a simple relational table to store this information:

FIRST (s#, status, city, p#, qty)

s# Supplier identification numberstatus Status code assigned to city

City City where supplier is locatedp# Part number of part supplied

Qty Qty of parts supplied to date

Composite primary key is (s#, p#)



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FIRST NORMAL FORM 1NFA relational table is said to be in the first normal form if all values of the columns

are atomic. That is, they contain no repeating values.

s# city status p# qty

s1 London 20 p1 300

s1 London 20 p2 100

s1 London 20 p3 200

s1 London 20 p4 100

s2 Paris 10 p1 250

s2 Paris 10 p3 100

s3 Tokyo 30 p2 300

s3 Tokyo 30 p4 200



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SECOND NORMAL FORM 2NF

Table FIRST contains redundant data. Redundancy causes update

anomalies.

Update anomalies - problems that arise when information is inserted,

deleted, or updated.

INSERT. The fact that a certain supplier (s5) is located in aparticular city (Athens) cannot be added until they supplied a part.

DELETE. If a row is deleted, then not only is the information about

quantity and part lost but also information about the supplier.

UPDATE. If supplier s1 moved from London to New York, then six

rows would have to be updated with this new information.




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A relational table is in second normal form 2NF if it is in 1NF and every non-key

column is fully dependent upon the primary key. That is, every non-key column

must be dependent upon the entire primary key.

FIRST is in 1NF but not in 2NF because status and city are functionally

dependent upon only on the column s# of the composite key (s#, p#).

Steps for transforming a 1NF table to 2NF is:

1.Identify any determinants other than the composite key, and the columns they

determine.

2.Create and name a new table for each determinant and the unique columns it

determines.

3.Move the determined columns from the original table to the new table.

Determinate becomes the primary key of the new table.

4.Delete the columns you just moved from the original table except for the

determinate which will serve as a foreign key.




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s# city status

s1 London 20

s2 Paris 10

s3 Tokyo 30

s# p# qty

s1 p1 300

s1 p2 100s1 p3 200

s1 p4 100

s2 p1 250

s2 p3 100

s3 p2 300

s3 p4 200

PARTS

SECOND




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Modification Anomalies Tables in 2NF but not in 3NF still contain modification

anomalies:

INSERT. The fact that a particular city has a certain

status (Rome has a status of 50) cannot be inserted until

there is a supplier in the city. DELETE. Deleting any row in SUPPLIER destroys the

status information about the city as well as the association

between supplier and city.




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THIRD NORMAL FORM 2NF

A relational table is in third normal form (3NF) if it is already in 2NF and every

non-key column is non transitively dependent upon its primary key.

In other words, all non-key attributes are functionally dependent onlyupon the primary key.

s# city status

s1 London 20

s2 Paris 10

s3 Tokyo 30

s4 Paris 10

SUPPLIERThe table supplier is in 2NF but not in

3NF because it contains a transitivedependencySUPPLIER.s# > SUPPLIER.citySUPPLIER.city > SUPPLIER.statusSUPPLIER.s# > SUPPLIER.status




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Steps for transforming a table into 3NF is:

1.Identify any determinants, other the primary key, and the columns theydetermine.2.Create and name a new table for each determinant and the unique

columns it determines.3.Move the determined columns from the original table to the new table. The

determinant becomes the primary key of the new table.

s# citys1 London

s2 Pariss3 Tokyos4 Pariss5 London

SUPPLIER

city status

London 20Paris 10Tokyo 30

Rome 50

CITY_STATUS

The transformation ofSUPPLIER into 3NF




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Advantages of 3rd Normal form :

Eliminates redundant data which in turn saves space and reducesmanipulation anomalies.

Example:

INSERT: Facts about the status of a city, Rome has a status of 50, can be added

even though there is not supplier in that city.

DELETE: Information about supplier can be deleted without destroying

information about a city.UPDATE: Changing the location of a supplier or the status of a city requires

modifying only one row.

s# citys1 London

s2 Pariss3 Tokyos4 Pariss5 London

SUPPLIER

city status

London 20Paris 10Tokyo 30

Rome 50

CITY_STATUS

The transformation ofSUPPLIER into 3NF




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Advanced Forms :: BOYCE CODD NORMAL FORM

Many practitioners argue that placing entities in 3NF is generallysufficient because it is rare that entities that are in 3NF are not also in

4NF and 5NF. The advanced forms of normalization are:

Boyce-Codd Normal FormFourth Normal Form

Fifth Normal FormBoyce-Codd normal form (BCNF) is a more rigorous version of the 3NF.

BCNF is based on the concept of determinants. A determinant column is

one on which some of the columns are fully functionally dependent.

A relational table is in BCNF if and only if every determinant is a

candidate key.



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Database DesignDatabase Design

This section presents and discusses How to translate the E-R (conceptual) model (diagram) to

an RDBMS (logical) schema. Exercise on E-R Modeling and Database Design

Some Guidelines - Entities: Create one table for each simple (not a sub-type or super-type)

entity. Attributes: Map each attribute to a candidate column with a more

precise format. Optional attributes become null columns Mandatory attributes become not null columns

Unique Identifier: Convert the components of the unique identifier tothe primary key of the table.


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b


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Database DesignDatabase DesignA few comments

There are more rules, treating exceptions, but these

are good enough in most cases

There may occur reasons to violate the rules.

Always: use common sense and expect iterativedevelopment.

Use CASE tools like ERWin wherever possible. Tools can

automatically generate SQL table definitions from

drawn E-R diagrams.

b i A i


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Database Design:: AssignmentDatabase Design:: Assignment

Develop an E-Rmodel and database

schema for a systemto handle purchaseorders.


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Creating a DB environment : SummaryCreating a DB environment : Summary The first step in designing a database application is to understand

what information the database needs to store and what integrityconstraints or business rules apply to the data.

Data Model is to a Database what a Building plan or a blueprint is to

a Building. It is the conceptual model of the Database.

Given a relational schema we need to decide whether it is a good

design or whether we need to decompose it into smaller relations.

Normalization gives the guidance to such decomposition.


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4.0 Structured Query Language4.0 Structured Query Language

Learning Objectives:At the end of this Topic you will be able to

Write simple SQL queries

Get familiar with the various relational operationssuch as SELECT,

PROJECT and JOIN

A d iA I d i


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An IntroductionAn Introduction

SELECT column-listFROM table-names WHERE condition(s)

Structured Query Language - (SQL) is the most widely

used commercial relational database language. The SQLhas several parts :

DML The Data Manipulation Language (DML)

DDL The Data Definition Language (DDL)

Embedded and dynamic SQL

Security

Transaction management

Client-server execution and remote database access


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Lord's Kitchen

Query ProcessingQuery ProcessingQuery Processing

Query in a High Level Language (typically a 4 GL)Parsing : The parser converts a query, submitted by

a database user and written in a high-levellanguage, into an algebraic operators expression.

Optimization : It is the key Topic for queryprocessing design. It receives the expression andbuilds a good execution plan. The plan determinesthe order of execution of the operators and selectssuitable algorithms for implementation of theoperators.

Code Generation for the Query : The planned codeis built with the aim of retrieving the result of thequery with high performance.

Code execution by Database Processor : The


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SELECT column-listFROM table-namesWHERE condition(s)

ConditionalSelection

Query ProcessingQuery Processing


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The SQL Select Statement performs three Types of Operations

SELECT column-listFROMtables-names

WHEREcondition(s)

1. Projection

3. Selection

2. Join

Query ProcessingQuery Processing


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Course No. Course_Title C_Hrs. Dept. C


MKT 333 Intro to Mkting 3 MKT

ECO 473 Labor Econ. 3 ECO

BA201 Intro to Stat. 5 ECOCIS 345 Intro to Dbase 4 CIS

Module

SELECT Module_Title, C_Hrs FROM Module

Course_Title C_Hrs.

Intro to CIS 4

Intro to Mkting 3

Labor Econ. 3

Intro to Stat. 5

Result Table

Performing ProjectionPerforming Projection


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Course No. Course T itle C. Hrs.Dep t. C


M KT 333 Intro to M kting 3 M KT

ECO 473 Labor Econ. 3 ECOBA201 Intro to Stat. 5 ECO

CIS 345 Intro to Dbase 4 CIS

Module

Course No. Course Title C. Hrs. Dept. C

CIS 120 Intro to CIS 4 CisCIS 345 Intro to Dbase 4 CIS

Result Table

Performing a Selection OperationPerforming a Selection Operation

SELECT * FROM Module WHERE C_Hrs = 4

Performing both Projection andPerforming both Projection and


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Course_No Course_Title C_ Hrs. Dept_C

CIS 120 Intro to CIS 4 CIS



BA201 Intro to Stat. 5 ECOCIS 345 Intro to Dbase 4 CIS

SELECT Module_Title, C_Hrs FROM Module WHERE Dept_C =CIS

Module

Course_Title C_ Hrs.

Intro to CIS 4Intro to Dbase 4

Result Table

Performing both Projection andg jSelectionSelection

Performing both Projection andPerforming both Projection and


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Basic SELECT Statement WHERE Clause OperatorsBasic SELECT Statement WHERE Clause Operators

=, , = IN (List) WHERE CODE IN (ABC, DEF, HIJ) - would return only rows

with one of those 3 literal values for the codeattribute

BETWEEN min_val AND max_val

WHERE Qty_Ord BETWEEN 5 and 15 - would return rows where Qty_Ord is >= 5 and


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Joining TablesJoining Tables

Joining TablesTo appropriately join tables, the tables must be

related and we apply a where clause which equatesthe primary key column of the table on the one sideof the relationship with the parallel foreign keycolumn of the many side table. This type of join is called an Equi-join. Our example will join Modules and departments where

dept code is the linking key column.

The next series of slides takes you through a step bystep process of combining data rows from one tablewith data rows in another table.

The first slide introduces the SQL Select statementthe shows the join operation and a picture of the

J i i T blJ i i T bl


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Course_No Course_Title C_Hrs Dept_Code


MKT 333 Intro to Mkting 3 MKTECO 473 Labor Econ. 3 ECO


CIS 345 Intro to Dbase 4 CIS

Dept Code Dept name Office#

MKT Marketing 244CIS Comp. Info. Sys. 302

ECO Economics 244

Module

Department

SELECT * FROM Module C, department DWHERE D.Dept_Code = C.Dept_Code

SQL will compare every row of the1st table with the first row of the 2ndtable. Then it will compare all rows of

the 1st with the second row of the second,and so on only rows where the condition

is met are placed in the result table.

Joining TablesJoining TablesJoining Two Tables - Select and Tables

J i i T blJ i i T bl


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Course_No Course_Title C_Hrs Dept_Code

CIS 120 Intro to CIS 4 CIS


ECO 473 Labor Econ. 3 ECOBA201 Intro to Stat. 5 ECO

n ro o ase

Dept Code Dept name Office#

MKT Marketing 244

CIS Comp. Info. Sys. 302

ECO Economics 244

ModuleDepartment

SELECT * FROM Module C, department D WHERE D.Dept_Code = C.Dept_Code

Course_No Course_Title C_Hrs Dept_Code Dept_Name Office#

RESULT TABLE

No match so row notplaced in results

Joining TablesJoining TablesJoining Two Tables - Row 1 Module to Row 1 Dept


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J i i T blJ i i g T bl


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Course _No Course _Title C_Hrs De pt_Code


MKT 333 Intro to M kting 3 MKT



ntro to aseDept Code Dept name Office#

MKT Marketing 244

CIS Comp. Info. Sys. 302

ECO Economics 244

Module

Department

SELECT * FROM Module C, department D WHERE D.Dept_Code = C.Dept_Code

Course_No Course_Title C_Hrs Dept_Code Dept_Name Office#

CIS 120 Intro to CIS 4 Cis Comp. Info S 302

RESULT TABLE

Joining Two Tables - Row 1 Module to Row 3 Dept

Joining TablesJoining Tables

5 0 Internal Management5 0 Internal Management


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5.0 Internal Management5.0 Internal Management

Learning Objective After completing this topic you will be able to :

Describe the various components of the computer systemthat provide data storage facilities to a DBMS

Understand how DBMS communicates with the host systemOutline some of the database tuning factors

Computer file management andComputer file management and


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DBMSDBMS Computer files are stored in external media such as disks and tapes.

Direct access Sequential access

Input output of data and memory management is managed by theOperating system File manager Disk manager

DBMS

File Request

File Manager

LogicalPage Req. Disk Manager

PhysicalPage Access

DBMS/Host inter-com

IntercommunicationIntercommunication


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IntercommunicationIntercommunication

DBMS/Host communication : A file is a collection of pages. A page is a unit of Input

Output.

The DBMS sends a file request to the file manager.

The file manager has no idea where the requested page isphysically stored.

The file manager in turn communicates with the disk

manager.

The file manager provides the database system with the

given page.

The database system converts the same into a logical form as

understandable by the user.

Tuning at the internal levelTuning at the internal level


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Tuning at the internal levelTuning at the internal level

Indexes Database indexes are important means of speeding up access

to set of records. Especially in a relational database. Index is very useful in existence tests.Once a index is created it is transparent to the user.

HashingHashing is directly determining a page address for a given

record without the overhead of creating indexes. The main problem associated with hashing are overflow &

underflow.Clusters

Physically storing related pages in the form of intra file

subsets. Inter file clustering to store records from distributed

databases in the same physical page.

Internal Management : S mmarInternal Management : Summary


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Internal Management : SummaryInternal Management : Summary

Database files are stored in logical page sets.The underlying physical files that store a database need not

map to the logical representation of the DBMS.

Indexes are useful means of speeding up data access in large

databases . They incur overheads.

Hashed functions speed up individual record access, however

has overflow & underflow problems.

Intra and inter file clustering of the physical records speed

up certain operations at the cost of other types of data

manipulations.

6 0 Database Trends6 0 Database Trends


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6.0 Database Trends6.0 Database Trends

Learning Objective At the end of this Topic you will be :

Familiar with various terms like

OLAP

Data warehousing Data mining

Aware of the business needs that require data to

be analyzed in multiple dimensions

Multidimensional Data AnalysisMultidimensional Data Analysis


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Multidimensional Data AnalysisMultidimensional Data AnalysisOn-line analytical processing (OLAP)

Multidimensional data analysis

Supports manipulation and analysis of large

volumes of data from multiple

dimensions/perspectives

Types of databases


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Lord's Kitchen

Major Types of DatabasesMajor Types of Databases

c e n t r a d i s t r i b n e t w o

D a t a

Centralized databaseCentralized database


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Centralized databaseCentralized databaseUsed by single central processor or multiple processors in client/server network

CPU DiskController

PrinterController

Tape driveController

Memory Controller

Memory

disk printerTape Drive

System bus

Distributed databaseDistributed database


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Distributed databaseDistributed database

Stored in more than one physical locationPartitioned database

Duplicated database

Multidimensional data model


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On-line analytical processing (OLAP)Multidimensional data analysis

Supports manipulation and analysis of large volumes of

data from multiple dimensions/perspectives

Data warehouse


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Supports reporting and query tools

Stores current and historical data Consolidates data for management analysis and decision making

Data warehouse


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Data mart

Subset of data warehouse

Contains summarized or highly focused portion of data

for a specified function or group of users

Data miningTools for analyzing large pools of data

Find hidden patterns and infer rules to predict trends

Databases and the web


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Hypermedia database

Organizes data as network of nodes

Links nodes in pattern specified by user

Supports text, graphic, sound, video and executable

programs

Databases and the web


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Database server

Computer in a client/server environment runs a DBMS to process

SQL statements and perform database management tasks

Application server

Software handling all application operations

Database Trends : SummaryDatabase Trends : Summary


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Database Trends : SummaryDatabase Trends : Summary

The database forms the backend for any kind ofapplication architecture be it a client server,

distributed system such as the web etc.

Users want to see data in as many dimensionspossible, therefore it is important to be aware

of concepts regarding Data warehousing , Data

mining and On-line analytical processing (OLAP)


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a a ase un amen a s: exa a ase un amen a s: exStepStep


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ResourceType

Description Reference Topic or Topic

Book Case*Method: Entity RelationshipModeling - Richard Barker

Book Data & Databases Joe Celko

Book An Introduction to Database Systems C. J. Date

Book The Data Modeling Handbook -Reingruber and GregoryBook Data Modeling for Information

Professionals Bob SchmidtBook Data Model Patterns David C. Hay,

Richard Barker


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