CS计算机代考程序代写 database 2021/8/8 Chapter 5 Data Modelling – Database Design – 2nd Edition

2021/8/8 Chapter 5 Data Modelling – Database Design – 2nd Edition

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DATABASE DESIGN – 2ND EDITION

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Chapter 5 Data Modelling
ADRIENNE WA�

Data modelling is the �rst step in the process of database design. This step is some-

times considered to be a high-level and abstract design phase, also referred to as

conceptual design. The aim of this phase is to describe:

The data contained in the database (e.g., entities: students, lecturers, courses,

subjects)

The relationships between data items (e.g., students are supervised by lecturers;

lecturers teach courses)

The constraints on data (e.g., student number has exactly eight digits; a subject

has four or six units of credit only)

In the second step, the data items, the relationships and the constraints are all ex-

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Preface


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Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

2021/8/8 Chapter 5 Data Modelling – Database Design – 2nd Edition

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pressed using the concepts provided by the high-level data model. Because these

concmepts do not include the implementation details, the result of the data mod-

elling process is a (semi) formal representation of the database structure. This result

is quite easy to understand so it is used as reference to make sure that all the user’s

requirements are met.

The third step is database design. During this step, we might have two sub-

steps: one called database logical design, which de�nes a database in a data model of

a speci�c DBMS, and another called database physical design, which de�nes the in-

ternal database storage structure, �le organization or indexing techniques. These

two sub-steps are database implementation and operations/user interfaces building

steps.

In the database design phases, data are represented using a certain data model. The

data model is a collection of concepts or notations for describing data, data relation-

ships, data semantics and data constraints. Most data models also include a set of

basic operations for manipulating data in the database.

Degrees of Data Abstraction

In this section we will look at the database design process in terms of

speci�city. Just as any design starts at a high level and proceeds to an ever-increas-

ing level of detail, so does database design. For example, when building a home, you

start with how many bedrooms and bathrooms the home will have, whether it will be

on one level or multiple levels, etc. The next step is to get an architect to design the

home from a more structured perspective. This level gets more detailed with respect

to actual room sizes, how the home will be wired, where the plumbing �xtures will

be placed, etc. The last step is to hire a contractor to build the home. That’s looking

at the design from a high level of abstraction to an increasing level of detail.

The database design is very much like that. It starts with users identifying the busi-

ness rules; then the database designers and analysts create the database design; and

then the database administrator implements the design using a DBMS.

The following subsections summarize the models in order of decreasing level

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Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

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of abstraction.

External models

Represent the user’s view of the database

Contain multiple different external views

Are closely related to the real world as perceived by each user

Conceptual models

Provide �exible data-structuring capabilities

Present a “community view”: the logical structure of the entire database

Contain data stored in the database

Show relationships among data including:

Constraints

Semantic information (e.g., business rules)

Security and integrity information

Consider a database as a collection of entities (objects) of various kinds

Are the basis for identi�cation and high-level description of main data objects;

they avoid details

Are database independent regardless of the database you will be using

Internal models

The three best-known models of this kind are the relational data model, the network

data model and the hierarchical data model. These internal models:

Consider a database as a collection of �xed-size records

Are closer to the physical level or �le structure

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Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

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Are a representation of the database as seen by the DBMS.

Require the designer to match the conceptual model’s characteristics and con-

straints to those of the selected implementation model

Involve mapping the entities in the conceptual model to the tables in the rela-

tional model

Physical models

Are the physical representation of the database

Have the lowest level of abstractions

Are how the data is stored; they deal with

Run-time performance

Storage utilization and compression

File organization and access methods

Data encryption

Are the physical level – managed by the operating system (OS)

Provide concepts that describe the details of how data are stored in the com-

puter’s memory

Data Abstraction Layer

In a pictorial view, you can see how the different models work together. Let’s look at

this from the highest level, the external model.

The external model is the end user’s view of the data. Typically a database is an en-

terprise system that serves the needs of multiple departments. However, one de-

partment is not interested in seeing other departments’ data (e.g., the human re-

sources (HR) department does not care to view the sales department’s data). There-

fore, one user view will differ from another.

The external model requires that the designer subdivide a set of requirements andPrevious: Chapter 4 Types of Data Models

Next: Chapter 6 Classi�cation of Database Management Systems

Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

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constraints into functional modules that can be examined within the framework of

their external models (e.g., human resources versus sales).

As a data designer, you need to understand all the data so that you can build an en-

terprise-wide database. Based on the needs of various departments, the conceptual

model is the �rst model created.

At this stage, the conceptual model is independent of both software and hardware. It

does not depend on the DBMS software used to implement the model. It does not

depend on the hardware used in the implementation of the model. Changes in either

hardware or DBMS software have no effect on the database design at the conceptual

level.

Once a DBMS is selected, you can then implement it. This is the internal model. Here

you create all the tables, constraints, keys, rules, etc.  This is often referred to as the

logical design.

The physical model is simply the way the data is stored on disk. Each database ven-

dor has its own way of storing the data.

Figure 5.1. Data abstraction layers.

Schemas

A schema is an overall description of a database, and it is usually represented by

the entity relationship diagram (ERD). There are many subschemas that represent
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Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

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external models and thus display external views of the data. Below is a list of items

to consider during the design process of a database.

External schemas: there are multiple

Multiple subschemas: these display multiple external views of the data

Conceptual schema: there is only one. This schema includes data items, rela-

tionships and constraints, all represented in an ERD.

Physical schema: there is only one

Logical and Physical Data Independence

Data independence refers to the immunity of user applications to changes made in

the de�nition and organization of data. Data abstractions expose only those items

that are important or pertinent to the user. Complexity is hidden from the database

user.

Data independence and operation independence together form the feature of data

abstraction. There are two types of data independence: logical and physical.

Logical data independence

A logical schema is a conceptual design of the database done on paper or a white-

board, much like architectural drawings for a house. The ability to change the logical

schema, without changing the external schema or user view,  is called logical data in-

dependence. For example, the addition or removal of new entities, attributes or rela-

tionships to this conceptual schema should be possible without having to change ex-

isting external schemas or rewrite existing application programs. 

In other words, changes to the logical schema (e.g., alterations to the structure of

the database like adding a column or other tables) should not affect the function of

the application (external views).Previous: Chapter 4 Types of Data Models

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Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

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Physical data independence

Physical data independence refers to the immunity of the internal model to changes

in the physical model. The logical schema stays unchanged even though changes are

made to �le organization or storage structures, storage devices or indexing strategy.

Physical data independence deals with hiding the details of the storage structure

from user applications. The applications should not be involved with these issues,

since there is no difference in the operation carried out against the data.

Key Terms

conceptual model: the logical structure of the entire database

conceptual schema: another term for logical schema

data independence: the immunity of user applications to changes made in

the de�nition and organization of data

data model:a collection of concepts or notations for describing data, data re-

lationships, data semantics and data constraints

data modelling: the �rst step in the process of database design

database logical design:  de�nes a database in a data model of a speci�c

database management system

database physical design: de�nes the internal database storage structure,

�le organization or indexing techniques

entity relationship diagram (ERD): a data model describing the database

showing tables, attributes and relationships

external model:  represents the user’s view of the database

external schema: user view

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Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

2021/8/8 Chapter 5 Data Modelling – Database Design – 2nd Edition

https://opentextbc.ca/dbdesign01/chapter/chapter-5-data-modelling/ 8/10

internal model: a representation of the database as seen by the DBMS

logical data independence: the ability to change the logical schema without

changing the external schema

logical design: where you create all the tables, constraints, keys, rules, etc.

logical schema: a conceptual design of the database done on paper or a

whiteboard, much like architectural drawings for a house

operating system (OS): manages the physical level of the physical model

physical data independence: the immunity of the internal model to changes

in the physical model

physical model: the physical representation of the database

schema: an overall description of a database

Exercises

���Describe the purpose of a conceptual design.

���How is a conceptual design different from a logical design?

���What is an external model?

���What is a conceptual model?

���What is an internal model?

���What is a physical model?

���Which model does the database administrator work with?

���Which model does the end user work with?

���What is logical data independence?

����What is physical data independence?

Also see Appendix A: University Registration Data Model ExamplePrevious: Chapter 4 Types of Data Models

Next: Chapter 6 Classi�cation of Database Management Systems

Chapter 4 Types of Data Models

Chapter 6 Classification of Database Management Systems

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Database Design – 2nd Edition by

Adrienne Watt is licensed under a

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This chapter of Database Design is a derivative copy of Database System

Concepts by Nguyen Kim Anh licensed under Creative Commons Attribution License

3.0 license

The following material was written by Adrienne Watt:

���Some or all of the introduction, degrees of data abstraction, data abstrac-

tion layer

���Key Terms

���Exercises

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