Lecture Notes 1(Data Modeling)

Lecture Notes 1

Data Modeling

1ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova, MSIT

• Database: A collection of related data.

• Data: Known facts that can be recorded and have an implicit meaning.– An integrated collection of more-or-less permanent data.

• Mini-world: Some part of the real world about which data is stored in a database. For example, student grades and transcripts at a university.grades and transcripts at a university.

• Database Management System (DBMS): A software package/ system to facilitate the creation and maintenance of a computerized database.

• Database System: The DBMS software together with the data itself. Sometimes, the applications are also included.

ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova, MSIT 2

Evolution of Database System


Ways of storing data

• Files – ancient times (1960)

• Databases

– Hierarchical (1970)


– Hierarchical (1970)

– Network (1970)

– Relational (1980)

– Object (1990)

File terms

– Record

• data items related to a single logical entity (e.g.

a student’s information) or row in a table

– Field


– Field

• a place for a data item in a record (first name

field in a student record) or a column in a table

– File

• a sequence of records of the same type (the

table)

File structures

ID Last First Grade

fieldA file: “STUDENT”


3 Smith Jane A

1 Wood Bob C

2 Kent Chuck B

4 Boone Dan B

ID Last First Grade

record

File organization

• Serial

– new records appended

• Sequential


• Sequential

– records ordered in file, usually according to a

numeric key

File structures

• Serial

– list of entries in

which the order of

entry into the list

3 Smith Jane A

1 Wood Bob C

ID Last First Grade


entry into the list

determines the

order of the list

1 Wood Bob C

2 Kent Chuck B

4 Boone Dan B

File structures

• Sequential

– list of entries

ordered in some 1 Wood Bob C

ID Last First Grade


ordered in some

way (e.g.

numerically or

alphabetically)

1 Wood Bob C

2 Kent Chuck B

3 Smith Jane A

4 Boone Dan B

Problems with files

– Redundancy

• number of files grows with applications, and data is duplicated

– Inconsistency

• data is updated in one application’s files, but not in


application’s files, but not in another’s

– Maintenance problems

• changes to data structures mean changes to many programs

– Difficulty combining data

• business needs may mean users want data from different applications

Data Modeling

• It is essential to building a good database.

• refers to the process where by data is

structured and organized.

• Once data is structured, it is usually then • Once data is structured, it is usually then

implemented into what is called a database

management system. The main idea behind

these systems to manage vast amounts of

both structured and unstructured data.


– Unstructured data include documents, word processing, e-mail messages, pictures, and digital video and audio files.

– Structured data, what is needed to make a data model (via a data model theory), is found in management systems like relational databases.

• Data Model• Data Model

– representations of different entity classes that a company wants to possess information about, containing the specifics behind that information, and the relationship among the differing entities and attributes.


– Both the blueprint and the foundation

– A representation of reality, a way to graphically

plot your data requirements

– A visual model of what your database can look like

when you get it implemented.

– the hardest and most important activity in the – the hardest and most important activity in the

RDBMS world. If you get the data model wrong,

your application might not do what users need, it

might be unreliable, it might fill up the database

with garbage.


Phases of Data Modeling

1. Conceptual Design Phase– Describes the concept of the database

– Graphically represents the data and information needs of the business

– Represents what the database can do and will do, – Represents what the database can do and will do, but not how it does it

– Will not show processes or activities related to the data

– Database designer uses an entity relationship diagram

– Vendor neutral and technology independent



2. Logical Design Phase

– You begin to convert or map the conceptual ERD to a more complete set of entities that begin to resemble tables.

– You also test to make sure the tables you – You also test to make sure the tables you designed are in third normal form or better, and you make decisions on record modification behavior

– Should also be technology and vendor independent



3. Physical Design Phase

– The logical model is converted to a specific

product platform

– Technology dependent– Technology dependent

– Sometimes designers combine the physical

design phase with the physical implementation

phase, the result brings a test database with a

set of tables representing the database entities


Common Data Models

• Hierarchical

• Network

• Relational

• Object• Object


Hierarchical database model


Hierarchical data model

ClassParent-child relationship (one-to-one or

Student

Grade

Instructor

ID

(one-to-one or one-to-many) among data

Department


Hierarchical data model

• Advantages

– easy to search

– add new branches easily

• Disadvantages

– must establish the types of search prior to

development of the hierarchical structure


Network data model


Network data model

ClassOne-to-one, one-to-many, many-to-one, or

Student

Grade

Instructor

ID

many-to-one, or many-to-many relationships possible

Department


Network data model

• Advantages

– flexible, fast, efficient

• Disadvantages

– Complex– Complex

– restructuring can be difficult because of

changing all the pointers


Relational database model

• Stores both

– Data about real

world objects world objects

(entities) in tables

– Relationships

between the

tables


Relational database

• Fields (columns) in the table store attributes. – Each attribute has a specific

domain.

• Tuples (or records or rows) in the table store

• Tuples (or records or rows) in the table store information. – Each tuple is a unique

instance of an object.

• Tables are composed of a set of tuples. – A table is also called a

relation.


Terms

• Table

– A collection of relevant data relating to one type of real world objects.

• Column

– A specific place for one type of data relating to one type of real world objects. type of real world objects.

• Domain

– Set of all possible values for a specific column.

• Row

– Collection of data describing one real world object.

• Primary Key

– Columns, which are part of the row and uniquely identify any one row.


Records

• Each record represents a logical entity (e.g. a

student)

• Each field represents an attribute of the logical

entityentity

1 Wood Bob C IST357

2 Kent Chuck B IST115

3 Smith Jane A IST357

4 Boone Dan B IST357

StudID Last First Grade Section

Student


Keys

• Each table has a primary key, one field (or a combination

of fields) that has a unique value for each and every

record in the table

Student

StudID is the primary

key in this table (two

students may share

either a last or first

name)

1 Wood Bob C IST357





Student


Relating tables

• Tables can be related (joined) together based on their keys

• The idea is to decompose into separate tables with no redundancy and to provide a capability to reassemble with no information loss

1 Wood Bob C IST357





Student

IST357 48 Jones

IST115 120 Brower

IST20 120 Fountain

Class

Section #Stud Instructor


Relating tables

Student

Class

Primary key Primary keyForeign key

1 Wood Bob C IST357





IST357 48 Jones

IST115 120 Brower

IST20 120 Mennis

Class



Relating tables

1 Wood Bob C IST357



Student

IST20 120 Brower

IST115 120 Jones

Class




IST115 120 Jones

IST357 48 Jones

Jones 332

Brower 517

Instructor

Name Office


Lecture Notes 1(Data Modeling)

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