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Data M odel4 A data model is a “description” of both a container for data and a methodology for storing and retrieving data from container.. The Relational Database• “A DBMS that manages

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This document describes all modules in Global Software Talent program for software tester

- Know Test plan structure; understand objective of each part and which part should be focus as a test team member

- Can study software requirement, get acquainted with and know how to ask questions to clarify requirement

- Write good test cases and effective defects

- Know how to report working progress and write test report

- Know what is automation test? Why automation test? When we use automation test? Automation test scripting techniques

Training program

Data M odel

4 A data model is a “description” of both a container for

data and a methodology for storing and retrieving data

from container

*4 “you can think of a data model as the infrastructure of the

data organizations, in other words, the way data is

presented to the user.”

Data model is

❖ Not a thing

❖You cannot touch it

❖ Data model are abstractions, mathematical algorithms &

Concepts

❖You can not touch a data model

Database Systems Models

Data base management systems follow particular

models (known as database models) to store and

manipulate

data A data base model is characterized by:

1 The way it stores data : S T R U C T U R E

2 The way data in the

structure are manipulated: O P E R A T IO N S

The Relational Database

• “A DBMS that manages data as collection of

tables in which all data relationships are

represented by common values in related

tables.”

• “A DBMS that follows all the twelve rules of

CODD is called RDBMS”

Tuple

s

Primary Key

* Attribute Value Set

Values currently contained in an attribute

« Relation I Table Degree:

Number o f attributes in a relation / table

« Tuples: Rows in a table / relation

« C a rd in a lity: Number of tuples in a relation / table

Ex: Instance of Students Relation

■ Do all values in each column of a relation instance have to be distinct?

Relational Database Concepts

Artist Pink Floyd

Field

STUDENT Name 1 SSN HomePtione Address OfliœPtoe Age GPA

/ * ■ Benjamin Bave»? Ị 305-61-2435 373-1616 2918 Bluebonnet Une nul 19 3.21

rows, of the table.

if no data exists for the relation

Hardware and Software

requirements are High

UNIX,VAX,VMS, etc

Examples are dBase, FOXBASE,

Examples are ORACLE,

JM GRESS, SQL Server 2000 etc

• Database design is the process of producing a detailed

data model of a database

• P rocess o f Database Design:

- Determine the relationships between the different

data elements

- Superimpose a logical structure upon the data on the

basis of these relationships

Database designs also include ER (Entity-relationship

model) diagrams

An ER diagram is a diagram that helps to design

databases in an efficient way

Entity Relationship Modeling

Sample E-R Diagram

Entity Relationship Modeling

Basic E-R Notation

Multivalued attribute Attribute

symbols , Derived attribute

Entity Relationship Modeling

Attributes

• Attribute - property or characteristic o f an entity type

• Classifications o f attributes:

- Simple versus Composite Attribute

- Single-Valued versus Multivalued Attribute

- Stored versus Derived Attributes

- Identifier Attributes

Entity Relationship Modeling

Identifiers (Keys)

• Identifier (Key) - An attribute (or combination of

attributes) that uniquely identifies individual

instances of an entity type

• Simple Key versus Composite Key

• Candidate Key - an attribute that could be a

key satisfies the requirements for being a key

• Characteristics of Identifiers:

- Will not change in value

- WII not be null

- No intelligent identifiers (e.g containing locations or people that might

change)

- Substitute new, simple keys for long, composite keys

Entity Relationship Modeling

A composite attribute

■H

Entity Relationship Modeling

Simple key attribute

- ■ :: : _

exactly one related entity

• One - to - Many: An entity on one side of the relationship can have many related entities, but an entity on the other side will have a maximum of one related entity

• Many - to - Many: Entities on both sides of the relationship can have many related entities on the other side

Cardinality Constraints - the number of instances of one entity that can or must be associated with each instance of another entity

• Minimum Cardinality

- If zero, then optional

- If one or more, then mandatory

• Maximum Cardinality: The maximum number

Optional (zero or one)

Entity Relationship Modeling

ER Model - Convert ER Models

to Relational schema (DB Design)

Rules for converting ER Model to

relational schema

• Basic Conversion Rules

• Entity Type Rule

• 1-M Relationship Rule

• M-N Relationship Rule

• Identification Dependency Rule

ER Model: DB Design Rule 2 - Example

v " y

Multivalued attribute becomes a

separate relation with foreign key

ER Model: DB Design Rule 3 - Example

ER Model: DB Design Rule 3 - Example

EMPLOYEE entity with

EMPLOYEE relation with

recursive foreign key

EMPLOYEE

Convert Unary relationship one to many

ER Model: DB Design Rule 3 - Example

ER Model: DB Design Rule 3 - Example

î FPT

to ^rnan

ER Model: DB Design Rule 3 - Example

A _

The Supplies

relationship will need to become a separate relation

ER Model: DB Design Another Converting Example

• Bad database designs results in:

- redundancy: inefficient storage

- anomalies: data inconsistency, difficulties in

maintenance

• Normalization is the process of efficiently

organizing data in a database with two goals:

- First goal: eliminate redundant data

• for example, storing the same data in more than one

table

- Second Goal: ensure data dependencies make sense

• for example, only storing related data in a table

Normalization Benefits o f Normalization

• Less storage space

• Quicker updates

• Less data inconsistency

• Clearer data relationships

• Easier to add data

• Flexible Structure

Normalization Update Anomalies

Relations that have redundant data may have

problems called update anomalies, which are

To insert a new staff with branchNo B007 into the

Normalization Update Anomalies - Example 2/2

Staff

s t a f f N o s N a m e p o s itio n s a la r y b r a n c e N o

between attributes in a relation

For example, if A and B are attributes of relation R, and B

is functionally dependent on A ( denoted A B), if each

value of A is associated with exactly one value of B ( A

and B may each consist of one or more attributes.)

Normalization Functional Dependencies 2/7

Trival fu n c tio n a l dependency means that the right-hand

side is a subset ( not necessarily a proper subset) of the left-

hand side

For example: (See Figure 1)

staffNo, sName -> staffNo They do not provide any additional information about possible integrity

constraints on the values held by these attributes.

because they represent integrity constraints for the relation.

Normalization Functional Dependencies 3/7

Main characteristics of functional dependencies in

normalization

• Have a one-to-one relationship between attribute(s) on

the left- and right- hand side of a dependency;

• hold for all time;

• are nontrivial

F u n ctio na l d e pe ndency is a property of the meaning or

semantics of the attributes in a relation When a

functional dependency is present, the dependency is specified as a

c o n s tra in t between the attributes.

An important integrity constraint to consider first is the

id e n tific a tio n o f candidate keys, one o f w h ic h is

selected to be the p rim a ry key for the relation using

functional dependency

Normalization Functional Dependencies 5/7 Inference Rules

A set of all functional dependencies that are implied by a given set of functional dependencies X is called closure

of X, written X+ A set of inference rule is needed to

Decomposition: If A -> B,C then A -> B and A-> C

Union: If A -> B and A -> C, then A-> B,C

C o n ^ ^ ^ U g m ^ ^ A - ^ B and C -> D then A.C-> B,

Normalization Functional Dependencies 6/7 Minial Sets o f Functional Dependencies

A s e t of functional dependencies X is m inim al if it satisfies

the following condition:

• Every dependency in X has a single attribute on its right-

hand side

• We cannot replace any dependency A -> B in X with

dependency C ->B, where C is a proper subset of A,

and still have a set of dependencies that is equivalent to

X

• We cannot remove any dependency from X and still

have a set of dependencies that is equivalent to X

Normalization Functional Dependencies 7/7 Example of A Minial Sets o f Functional

Dependencies

A set of functional dependencies for the StaffBranch

relation satisfies the three conditions for producing a

Normalization The Process o f Normalization

Normalization is often executed as a series of

steps Each step corresponds to a specific

normal form that has known properties.

As normalization proceeds, the relations become

progressively more restricted in format, and also

less vulnerable to update anomalies.

For the relational data model, it is important to

recognize that it is only first normal form (1NF)

that is critical in creating relations All the

subsequent normal forms are optional.

Normalization

First Normal Form - 1 N F

structure

• Rules

• Define the data items required, because they

become the columns in a table Place related

data items in a table.

• □ Ensure that there are no repeating groups of

data.

• □ Ensure that there is a primary key.

Normalization 1NF Example

Normalization 1NF Disadvantage

Các bất thường của quan hệ ở 1NF

► Thêm vào

• Không thể thêm thông tin của sinh viên mới có mã là

S4, ten là Thành, thuọc lớp có mã là L í nếu sinh viên

này chưa đăng ký học môn học nào cả

► Cập nhật

• Sửa tên của sinh viên có tên là Tiến với tên mới là

Thành sẽ phải sửa tất cả các hàng của sinh viên này.

► Xóa bỏ

• Xộa thông tin sinh viên S3 đăng ký môn học M1 sẽ làm

mất thông tin của sinh viên này~

Second Normal Form - 2NF

table is either dependent on the whole of a candidate

key, or on another non prime attribute

Normalization 2NF Example

Lưọ'c đồ quan hệ R không ờ 2NF vì thuộc tính không khóa Họtên phụ

thuộc hàm riêng phần vào khóa {Mãsv, Mônhọc}.

Normalization 2NF Example

Khóa của Ri: Mãsv

đều phụ thuộc hàm đầy đủ vào khóa.

Normalization 2NF Disadvantage

❖ Các bất thuửng của quan hệ ở 2NF

► Thêm vào

• Không thể thêm thông tin của lớp L3 có tên là MT03

nếu chưa có sinh viên nào học lớp này

► Cập nhật

• Sửa tên của lớp có mã /.í với tên mới là MT_1 sẽ phải

sửa tất cả các hàng của lớp này

Normalization 3NF - Example

Lược đồ quan hệ Rì không ở 3NF vì thuộc tính không khóa Tért/óp

phụ thuộc bắc cầu vào khóa Mãsv.

Mẵlớp -/-> Măsv Tênióp Ể {Mãsv, Mălớp}

Normalization 3NF - Example

Khóa của R12: Mãsv

đều không phụ thuộc bắc cầu vào khóa.

Paymentl Amount: currency

Paymentl Type: ehar(4)

Paymentl Description; chai{40i

Normalization - 2NF

D on’t d e sig n a database th a t copes w ith th e norm

C hoose m ea nin g fu l nam es fo r tables and fie ld s.

T ry to keep nam es sim ple

Be c o n s is te n t in y o u r nam ing and ch o ice o f data

type.

A nalyze y o u r data needs on paper firs t.

P ick y o u r p rim a ry key ca re fu lly.

Create an index

A d d a m u ltic o lu m n index.

A v o id u sin g reserved w o rd s as table o r fie ld names

C o n sid e r storage space requirem ents.

Q & A

_ _

Question 1

Consider the following relations for a database that keeps track of student enrollment in courses and the books adopted for each course (Primary Key is mark post-fix with #):

STUDENT(SSN#, Name, Major, Bdate)

COURSE(Course#, Cname, Dept)

ENROLL(SSN, Course#, Quarter, Grade)

BOOK_ADOPTION(Course#, Quarter, BookJSBN)

TEXT(Book_ISBN#, Book_Title, Publisher, Author)

Draw a relational schema diagram specifying the foreign keys for this schema

rotation

Please:

□ Data Definition Language (DDL)

□ Data Manipulation Language (DML)

• Primary function is to store and retrieve data as requested by other software applications.

• Query Analyzer: one of the Ms SQL Server that:

- Allows us to write queries and SQL statements

- Checks syntax of the SQL statement written

- Executes the statements

- Store and reload statements

- Save the results in file

- View reports (either as grid or as a text)

Integer : Stores whole number

Float : Stores real numbers

Text : Stores characters

Decimal : Stores real numbers

Money : Stores monetary data Supports 4 places

after decimalDate : Stores date and time

Binary : Stores images and other large objects

Miscellaneous : Different types special to SQL Server (Refer to notes for more info)

SQL (Structured Query Language) is the standard for

relational database management systems (RDBMS)

SQL-92 and SQL-99 Standards - Purpose:

- Specify syntax/sem antics for data definition and

manipulation

- Define data structures

- Enable portability

- Specify minimal (level 1) and complete (level 2) standards

- Allow for later growth/enhancem ent to standard

What Can SQL do?

- Retrieve, insert, update, and delete database records

- Create new or update database structures: table, view,

stored procedures, etc.

- Grant access permission to database objects: tables, stored

procedures, views, etc.

SQL Overview SQL Environment

SQL Overview SQL Database Objects

• A SQL Server database has lot of objects like

SQL Overview SQL Database Objects (Cont)

Tables Views procedures Functions

Accept parameters to perform operations

The return value can either be a single value

Based on SELECT queries

Contain statements that perform operations

Vw.

Do not return values

Triggers

Special kind

of stored procedure that automatically executes when an event occurs

in the database server

- Creates a table with tw o colum ns

Drop table tablename;

- Drops the table structure

the type of data that can go into a table.

• We will focus on the following constraints:

to verify regular data.

• Syntax:

• Sample:

ALTER TABLE [dbo].[Products] ADD

CONSTRAINT [CK_Products_No_Nissan] CHECK ([Productname] <> 'nissan sentra')

Data Definition Language

* PRIMARY constraint: used to specify prim ary key of

table.

• Syntax:

PRIMARY KEY [(danh_sach_cot)]

Data Definition Language Table Constraint Scope

•Column Level

CREATE TABLE [dbo].[Customers] (

[CustomerlD] [int] IDENTITY (1, 1) NOT NULL PRIMARY KEY ,

[CustomerEmail] [varchar] (30) NULL ,

[CustomerState] [varchar] (5) NULL

) ON [PRIMARY]

GO

•Table Level

ALTER TABLE [dbo] [Products] ADD

CONSTRAINT [PK_Products] PRIMARY KEY CLUSTERED

(

[ProductID], [ProductName]

GO