oracle

Database Fundamentals

Database Fundamentals

Basic & Intermediate

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

Module Outline

4.Structured

Query Language

2.Types of

Database Systems

3.Creating a Database

Environment

5.Internal

Management

1.What is a

Database System

6.Database

Trends

1.0 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

What is a Database System A Database System is essentially a

computerized record-keeping system.

A database-management system (DBMS)

consists of a collection of interrelated data and a

set of programs to access those data.

Database systems are designed to manage

large volume of information

File 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 complete number

Byte: Group of bits that represents a single character

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

Data Hierarchy in a Computer System


Entity: Person, place, thing, event about which information is maintained

Attribute: Description of a particular entity

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


Data redundancy

Program-Data dependence

Lack of flexibility

Poor security

Lack of data-sharing and availability

No concurrency control

Problems with the Traditional File Environment

Traditional File Processing

DBMS and its Advantages

• A Database Management System is a collection of programs that

enables users to create and maintain a database. It is a general purpose

software system that facilitates processes of defining, constructing and

manipulating databases for various applications.

• Advantages 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

Acts as an interface between

application programs and physical

data files.

Separates logical and physical

views of data

Eliminates redundancy of data

Creates and maintains databases

Enforces security of data

Figure 7-4

Database Management System (DBMS)

DBMS Architecture

• Internal Schema : Describes physical storage structure of database

• Conceptual Schema : Describes structure of whole database for a community of users.

• External Schema : Each view describes that part of database that a particular user requires, and hides the rest.

DBMS Architecture

• 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.

Functions of DBMS

• Data definition : • Specifies content and 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

Requirements of a DBMS

Key elements in a database environment:

• Data Administration

• Data Planning and Modeling Methodology

• Database Technology and Management

• Users

Database System : Recap• Why 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

Quiz

If a Customer Database has the following fields : EmpId, EmpName, Salary and DeptName, What would be the ideal Key field and why ?

EmpIDEmpNameDeptNameEmpId+DeptName

2.0 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 DBMS

• Hierarchical DBMS

• Network DBMS

• Object-Oriented Databases

Relational Database Model

• Represents data as two-dimensional tables called relations• Relates data across tables based on common data element

Examples: DB2, Oracle, MS SQL Server

• Select: Creates subset of rows that meet specific criteria

• Join: Combines relational tables to provide users with information

• Project: Enables users to create new tables containing only relevant information

Three Basic Operations in a Relational Database

Three Basic Operations in a Relational Database

SELECT

PROJECT

JOIN

Hierarchical Database Model• It is a pointer based model• Organizes data in a tree-like structure • Stores data in tables and views relationships as links• Supports one-to-many parent-child relationships• Prevalent in large legacy systems

Network DBMS

Depicts data logically as many-to-many relationships Organizes data in tables and views relationships as links It is also a pointer based model Organizes data in arbitrary graphs

Hierarchical and Network DBMSSome of the Disadvantages Outdated

Complex pointer based organization

Less flexible compared to RDBMS

Lack support for ad-hoc and English language-like

queries

Object-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

Types of Databases : Summary

• In a relational database the data is

perceived as tables (and nothing but

tables) by the user

• The relational operators available are used

to manipulate the data in the tables

3.0 Creating a DB environment

Learning Objective:

At the end of this Topic you will –

• Have the ability to model an application system based

on the E-R Modeling approach.

• Understand the Relational Database concepts like

Normalization, 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.

Introduction to Data Modeling What 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

• An Overview :

• Conceptual representation of the data structures required by

a database

• Data structures include the data objects, the associations

between data objects, and the rules which govern operations

on the objects

• 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 is to a Building

• A Database Design translates a data model into a database

• A Data Model is the conceptual design of a database

Introduction to Data Modeling

E-R Modeling

Originally proposed by Peter Chen (1976)

Views the real world as entities and relationships

Key component is the E-R Diagram

Most 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 an

instance

(occurrence) of an entity

Entity relationship diagram

has works for• Dept No.

• Name

• Name• Emp Id.

Entity

Relationship Attributes

EMPLOYEEDEPARTMENT

Identifier

E-R Modeling

• 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

E-R Modeling

• 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 independent entity 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

E-R Modeling

• 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

E-R Modeling

ORDER ITEMORDER LINEappears onfor ahas

belongs to

E-R Modeling

Example of Associative entity :

• Generalization Hierarchies

• Generalization occurs when two or more entities

represent 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

E-R Modeling


• 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.

E-R Modeling


• Sub-types can be either mutually exclusive (disjoint) or overlapping

(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

E-R Modeling

PERSON

FACULTYSTUDENT STAFF


• In a disjoint hierarchy, an entity instance can

be in only one subtype.

Example: Entity EMPLOYEE, may have two subtypes,

CLASSIFIED and WAGES. An employee may be one

type or the other but not both

E-R Modeling

• Generalization Hierarchies - Nested

E-R Modeling

PERSON

FACULTYSTUDENT

UNDERGRAD GRADUATE

E-R Modeling• Attribute

• Attributes 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 attribute

Contains only atomic values• Composite attribute

Has component attributes

Student Name

FName

LName

MI

DOB

Simple Composite

E-R Modeling

• 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

Module

Student

Math

PhysicsId

Multi-valued

Single-valued

E-R Modeling

• Identifiers and Descriptors

• Attributes can be classified as identifiers or descriptors

• Identifiers, more commonly called keys, uniquely identify an

instance of an entity.

• A descriptor describes a non-unique characteristic of an entity

instance.

An Example :

Entity: Employee

Unique Identifier: Employee No.

Descriptor: Name, DOJ, DOB

E-R Modeling

• 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

• Degree• Number of entities associated with the relationship • Binary 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.

E-R Modeling

E-R Modeling• 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

E-R Modeling

• 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

• 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.

E-R Modeling

• Existence• Denotes 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 be included 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

E-R Modeling

• 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

E-R Modeling

E-R Modeling

• Entities• Represented by labeled rectangles• The 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 Modeling

• 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

Employee• EmpID

• EmpName

E-R Modeling : AssignmentHow 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…

Step 1: Identify Entities• Entities

Purchase Order (PO)Buyer?VendorLine ItemsSales OrderApproval Limit?

• Buyer characterizes a PO• Approval Limit characterizes a Buyer

What does it tell us?

• Approval Limit is not an entity• Buyer is an entity• Approval Limit is an attribute of the entity Buyer

E-R Modeling

Step 2: Identify Relationships

Look for phrases describing a link between two things or

objects

Verbs relating two nouns often suggest relationships

e.g. A buyer creates a purchase order, A purchase order

has one or more

Lines

Requirements may or may not contain information

regarding degree,

existence, cardinality of a relationship up front

Further questioning may need to be done to determine

the above

E-R Modeling

Step 2: Identify Relationships

PO

PO replaced by Buyer

Buyer creates a is approver of

Vendor

Vendor supplies against a

- - Line

Line belongs to a - created for item supplied by

-

E-R Modeling

Grid Technique

Step 2 : Identify Relationships• Analyzing Existing Systems (Files, Databases)• Look for -

Pointers Foreign Keys Repeating Groups Structured Codes

• All of the above imply relationships

E-R Modeling

• 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

E-R Modeling

• Step 3: Identify Attributes

E-R Modeling

Purchase Order No __________ Buyer _________ Vendor ___________ Date Created ______

No Item Quantity Value___ ___________ ______ _____________ ___________ ______ _____________ ___________ ______ __________

Shipping AddressStreet _________City __________Zip _______ Total Value ______

Example Purchase Order Form• Purchase Order No• Vendor • Buyer• Date Created• Item?• Address• City• State• Zip• Total Value?

E-R Model of the Purchase Order Example

PURCHASE ORDER

VENDOR

BUYERcreates

created by

supplies against

created for a

LINE

has

belongs to

ITEM

created for

exists on

E-R Modeling

Major Modeling Techniques Peter Chen’s original entity/relationship

diagrams Information Engineering Richard Barker’s notation, used by Oracle

corporation IDEF1X Object Role Modeling Unified Modeling Language (UML) Extensible Markup Language (XML)

E-R Modeling

E-R Modeling

• Major Modeling Techniques

• Data 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

Relational 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.

Relational Model

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

Tables, Columns and Rows Relationships and Keys Data Integrity Normalization What is a table?

• Represents some real-world person, place, thing, or event

• Two-dimensional• Columns• Rows

Relational Model

Course No. Course_Title C_Hrs. Dept. C

CIS 120 Intro to CIS 4 Cis

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

Table• Columns represent a property of the person, place, thing or

event that the table represents• Rows represent an occurrence or instance of what the

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

column• Each named column has a domain, which is the set of

values that may appear in that column

Relational Model

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 101412

102739 Scott C1 4/13/01 101667

Employee

Relational Model

In this document

Formal Terms Many Database Manuals

Table Relation Table

Column Attribute Field

Row Tuple Record

Table - Terminology

Relational Model

• 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

Relational Model

• 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

Relational Model

• Data Integrity

• Ensures correct and consistent navigation and manipulation of

relational 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

Relational Model

• 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

Relational Model

• Selection• The select operator, sometimes called restrict to prevent confusion 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

Relational Model• Projection

• The project operator retrieves subsets of columns from a relational table removing duplicate rows from the result

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

Relational Model

k x y

1 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, is the

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

Relational Model

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

another or same table• Criteria 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 removed Joins can also be done on criteria other than equality. Such joins are called non-equi joins

k a b1 A 2

2 B 4

3 C 6

k c1 aa

3 bb

5 cc

k a b k c

1 A 2 1 aa

3 C 6 3 bb

k a b c

1 A 2 aa

3 C 6 bbTable A

Equi-JoinTable B

Natural Join

Relational Model• Union

• 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 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 y1 A 2

2 B 4

3 C 6 k x y1 A 2

4 D 8

5 E 10

k x y1 A 2

2 B 4

3 C 6

4 D 8

5 E 10

A Union B

Relational Model• 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 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 y1 A 2

2 B 4

3 C 6 k x y1 A 2

4 D 8

5 E 10

k x y1 A 2

2 B 4

3 C 6

4 D 8

5 E 10

A Union B

Relational Model• Intersection

• The intersection of two relational tables is a third table that contains 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 y1 A 2

2 B 4

3 C 6

k x y1 A 2

4 D 8

5 E 10k x y1 A 2

Table A

Table B

A Intersect B

Relational Model• Difference

• The difference of two relational tables is a third that contains those rows

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 6

Table A

Table B

A MINUS B

k x y

1 A 2

4 D 8

5 E 10

B MINUS A

k x y2 B 4

3 C 6

k x y4 D 8

5 E 10

Relational Model

Table A Table B

A DIV B

• Division• The division operator results in columns values in one table for which

there are other matching column values corresponding to every row in another table.

k x y1 A 2

1 B 4

2 A 2

3 B 4

4 B 4

3 A 2

x yA 2

B 4

k1

3

NormalizationNormalization theory is based on the concepts of normal forms. A relational table is said to be a particular normal form if it satisfied a certain set of constraints.

We shall discuss four normal forms in this Module.

The concept of functional dependency is the basis for the first three normal forms.

A column Y of a relational table is said to be functionally dependent upon 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.

Normalization

Un normalizedRelation

NormalizedRelation (1NF)

2 NF

3 NF

Boyce/Codd NF

Removerepeating groups

Remove partial dependencies

Remove transitive dependencies

Remove remaining Anomalies resulting from FD‘s

Remove multivalueddependencies

Normalization

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 number status Status code assigned to city City City where supplier is located p# Part number of part supplied Qty Qty of parts supplied to date

Composite primary key is (s#, p#)

Normalization

• FIRST NORMAL FORM –1NF

A 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

Normalization• 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 a particular 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.

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.

Normalization

Normalization• SECOND NORMAL FORM – 2NF

• 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.

Normalization

SECOND NORMAL FORM – 2NF

s# city statuss1 London 20

s2 Paris 10

s3 Tokyo 30

s# p# qtys1 p1 300

s1 p2 100

s1 p3 200

s1 p4 100

s2 p1 250

s2 p3 100

s3 p2 300

s3 p4 200

PARTS

SECOND

Normalization

• 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 only upon the primary key.

s# city statuss1 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 transitive dependencySUPPLIER.s# —> SUPPLIER.citySUPPLIER.city —> SUPPLIER.statusSUPPLIER.s# —> SUPPLIER.status

Normalization• Steps for transforming a table into 3NF is:

1. Identify any determinants, other the primary 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. The determinant becomes the primary key of the new table.

s# city

s1 London

s2 Paris

s3 Tokyo

s4 Paris

s5 London

SUPPLIER

city status

London 20

Paris 10

Tokyo 30

Rome 50

CITY_STATUS

The transformation of SUPPLIER into 3NF

Normalization• Advantages of 3rd Normal form :

• Eliminates redundant data which in turn saves space and

reduces manipulation 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# city

s1 London

s2 Paris

s3 Tokyo

s4 Paris

s5 London

SUPPLIER

city status

London 20

Paris 10

Tokyo 30

Rome 50

CITY_STATUS

The transformation of SUPPLIER into 3NF

Normalization• Advanced Forms :: BOYCE CODD NORMAL FORM

Many practitioners argue that placing entities in 3NF is generally

sufficient 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 Form

Fourth Normal Form

Fifth Normal Form

Boyce-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.

Database 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 to the primary key of the table.

Database Design

• Sub-types: A sub-type entity is simply an entity with its own attributes

or relationships, but it also inherits any attributes and/or relationships

from its parent entity (super-type)

• 1:1 relationships: Merge the two entities into a single table, keeping

all attributes. Identify (add if needed) the primary key.

• 1:Many relationships: Create two tables, one for each entity. Post

the primary key from the 1 side to the N side (add attributes), and

identify it as a foreign key. (Add the primary key from the 1 side to the

attributes on the Many side. The posted attributes are a foreign key.)

• M:N (Many:Many) relationships: Create a new (bridge) table and

post the primary keys from both entities as attributes in the new table.

The posted attributes are foreign keys.

Database Design

A 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 iterative

development.

Use CASE tools like Erwin wherever possible. Tools

can automatically generate SQL table definitions

from drawn E-R diagrams.

Database Design:: Assignment

Develop an E-R model and database schema for a systemto handle purchase orders.

Creating a DB environment : Summary

The first step in designing a database application is to

understand what information the database needs to store and

what integrity constraints 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.

4.0 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 operations such as SELECT,

PROJECT and JOIN

An Introduction

SELECT column-list FROM table-names WHERE condition(s)

• Structured Query Language - (SQL) is the most widely used commercial relational database language. The SQL has 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

Query 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-level language, into an algebraic operators expression.• Optimization : It is the key Topic for query processing design. It receives the

expression and builds a good execution plan. The plan determines the order of execution of the operators and selects suitable algorithms for implementation of the operators.

• Code Generation for the Query : The planned code is built with the aim of retrieving the result of the query with high performance.

• Code execution by Database Processor : The query plan is executed by the execution engine Topic that delivers the result for the user.

• Result of the Query

Query Processing

Query Processing

137150

Door latchDoor seal

22.506.00

SELECT column-list FROM table-names WHERE condition(s)

Conditional Selection

Query Processing

• The SQL Select Statement performs three Types of Operations

SELECT column-list FROM tables-names

WHERE condition(s)

1. Projection

3. Selection

2. Join

Course No. Course_Title C_Hrs. Dept. C

CIS 120 Intro to CIS 4 CisMKT 333 Intro to Mkting 3 MKTECO 473 Labor Econ. 3 ECOBA201 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 4Intro to Mkting 3Labor Econ. 3Intro to Stat. 5Intro to Dbase 4

Result Table

Performing Projection

SELECT * FROM Module WHERE C_Hrs = 4

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



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

Course_No Course_Title C_ Hrs. Dept_C

CIS 120 Intro to CIS 4 CISMKT 333 Intro to Mkting 3 MKTECO 473 Labor Econ. 3 ECOBA201 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 and Selection

• Basic 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 code attribute

• BETWEEN min_val AND max_val• WHERE Qty_Ord BETWEEN 5 and 15 - would return rows where• Qty_Ord is >= 5 and <= 15 - Works on character data using ascending

alphabetical order• LIKE “literal with wildcards” % used for multiple chars. _ single char.

• WHERE Name LIKE ‘_o%son’ - returns rows where name has o as the 2nd character and ends with son - Torgeson or Johnson

• NOT• WHERE NOT Name = ‘Johnson’ - would return all rows where name <>

Johnson - lowest priority in operator order • AND and OR, Use Parentheses to control order

Performing both Projection and Selection

Joining Tables

• To appropriately join tables, the tables must be related and we apply a

where clause which equates the primary key column of the table on the one

side of the relationship with the parallel foreign key column 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 by step process of

combining data rows from one table with data rows in another table.

• The next slides show progressive steps in the join process.

• The first slide introduces the SQL Select statement the shows the join

operation and a picture of the two tables that the join will operate on.

Joining Tables

Joining Two Tables - Select and Tables

Course_No Course_Title C_Hrs Dept_Code





Dept Code Dept name Office#MKT Marketing 244CIS Comp. Info. Sys. 302ECO Economics 244

Module

Department

SELECT * FROM Module C, department D WHERE 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 Tables

Joining Two Tables - Row 1 Module to Row 1 Dept


CIS 120 Intro to CIS 4 CIS





ModuleDepartment


Course_No Course_Title C_Hrs Dept_Code Dept_Name Office#

RESULT TABLE

No match so row notplaced in results

Joining Tables








ModuleDepartment



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

RESULT TABLE

Match on conditioncauses a result row tobe produced.

Joining Tables






BA201 Intro to Stat. 5 ECOCIS 345 Intro to Dbase 4 CIS Dept Code Dept name Office#

MKT Marketing 244CIS Comp. Info. Sys. 302ECO Economics 244

ModuleDepartment



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

RESULT TABLE

Joining Tables

5.0 Internal Management

Learning Objective

After completing this topic you will be able to :

Describe the various components of the computer

system that provide data storage facilities to a

DBMS

Understand how DBMS communicates with the

host system

Outline some of the database tuning factors

Computer file management and DBMS 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 the Operating system • File manager• Disk manager DBMS

File Request

File Manager

Logical Page Req Disk Manager

Physical Page Access

DBMS/Host inter-com

Intercommunication 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 is

physically 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 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.

Hashing• Hashing 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 : 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 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 Analysis

• On-line analytical processing (OLAP)

• Multidimensional data analysis

• Supports manipulation and analysis of large

volumes of data from multiple

dimensions/perspectives

• Major Types of Databases

cen tra lised d a tab ases d is trib u ted d a tab ases n e tw ork d a tab ases

D atab ases

Types of databases

Used by single central processor or multiple processors in

client/server network

CPU Disk Controller Printer Controller

Tape driveController

Memory Controller

Memory

disk printerTape Drive

System bus

Centralized database

Stored in more than one physical location• Partitioned database • Duplicated database

Distributed database

On-line analytical processing (OLAP)• Multidimensional data analysis

• Supports manipulation and analysis of large volumes

of data from multiple dimensions/perspectives

Multidimensional data model

Supports reporting and query tools

Stores current and historical data

Consolidates data for management analysis and

decision making

Data warehouse

Data mart• Subset of data warehouse

• Contains summarized or highly focused portion of

data for a specified function or group of users Data mining

• Tools for analyzing large pools of data

• Find hidden patterns and infer rules to predict trends

Data warehouse

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

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

Databases and the web

Database Trends : Summary The database forms the backend for any kind

of application architecture be it a client

server, distributed system such as the web

etc.

Users want to see data in as many

dimensions possible, therefore it is important

to be aware of concepts regarding Data

warehousing , Data mining and On-line

analytical processing (OLAP)

Database Fundamentals: Next Step

Resource Type

Description Reference Topic or Topic

Book Case*Method: Entity Relationship Modeling - Richard Barker

Book Data & Databases – Joe Celko

Book An Introduction to Database Systems – C. J. Date

Book The Data Modeling Handbook - Rein Gruber and Gregory

Book Data Modeling for Information Professionals – Bob Schmidt

Book Data Model Patterns – David C. Hay, Richard Barker

Education

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