Database Modeling I

The cautious seldom err. Confucius

Class Outline What are the steps in designing databases? How does one collect information necessary to design a

database? Why is modeling important? What are the basic elements of a database model? How are the following represented in a database model?

entity attribute degree of relationship connectivity cardinality binary M:N relationships participation

A good designer combines the art of design with the science of design.

Characteristics of a Database designer Knowledge of the problem you are trying to solve

Communication skills - extensive discussions with users

Analytical aptitude - keep in mind the broad goals even while

poring over the smallest details

Impertinence - question everything!

Impartiality - find best solution

Relax constraints - assume anything is possible

Pay attention to details and definitions

Reframing - iteratively analyze in new way - be creative!

1. Define the problem and define database objectives

2. Analyze current database, assess user requirements, and create data model

3. Design data structures (tables, fields, field specifications, establish keys)

4. Establish table relationships

5. Clarify business rules critical to database design (e.g., required fields, validation rules)

6. Determine and establish user views of data

7. Review data integrity and reiterate design methodology

Conceptual Design Methodology

Statement of Purpose

1.Declare a specific purpose for the database to focus and guide its developmente.g., “The purpose of the All-Star Talent database is to maintain the data we use in support of the entertainment services we provide to our clientele.”

2.Articulate goals & objectives that define specific tasks“We need to maintain complete entertainer information.”

“We need to maintain complete customer information.”

“We need to track all customer-entertainer bookings.”

“We need to maintain financial records of both payments from customers and payments to entertainers.”

Assessment of User Requirements:What is analyzed?

interview transcripts meeting minutes observational notes business mission and

strategy statements questionnaire results

document analyses business forms reports flow charts presentations computer-generated output training manuals consultant reports job descriptions

Assessment of User Requirements:Specific requirements

What are subjects/objects for the business? What characteristics describe each object? What unique characteristic distinguishes each object from other objects

of the same type? How do you use this data (e.g, summary reports)? Over what period of time are you interested in this data? Are all instances of each object the same? What events occur that imply associations between various objects? Is each activity or event always handled the same way or are there

special circumstances?

Goals of analysis of user requirements: collect a list of business goals, entities to track, a database schema, and sample report outputs.

Rules for Conducting User Interviews Create a quiet, stress-free environment; set a limit of six people Have an agenda - provide it to participants ahead of time Focus on the problem at hand; maintain control of the interview Conduct separate interviews for users and management Identify the decision maker Avoid technical jargon Show concern for user needs Give everyone equal and undivided attention Write down everything where it can be seen by participants Encourage ‘blue sky’ thinking Arbitrate disputes Keep the pace of the interview moving Don’t foreclose your options too soon

Data Modeling A model is a simplified representation (usually a graphic) of a

complex object in reality to make it understandable If the elements in the model are correctly associated with

elements in reality, the model can be used to solve problems in reality (e.g., engineer’s model to determine a bridge’s weight tolerance; if the model is incorrect...)

an ER model is integrated set of concepts that describes data, relationships between data, and the constraints on the data as they are used within a specific organization; a data model renders organization’s (users’) view of objects and/or events and their associations

ER model is a blueprint from which a well-structured database is created

ER models are independent of details of implementation

E-R Modeling Concepts

Objects

Entities

Relationships

Attributes

Relationship Type

Degree

Values

Domains

1 : 1

1 : N

M : N

Mandatory

Optional

Connectivity

Participation

Recursive

Binary

Ternary

N-ary

Cardinality

Entities Entity

Something that can be identified in the users’ environment about which we want to store data; typically is a noun

Entities or objects must have occurrences that can be uniquely identified

Identified by an organization or its users Consists of tangible or intangible objects or events

Entity Instance A single entity occurrence or instance within a collection of

entities

e.g., STUDENT is an entity; Annie Abel is an entity instance as are Bob Brown and Cathy Chen.

STUDENT

Attributes properties that describe characteristics of an entity - assumed all

instances of a given entity have the same attributes use atomic attributes, those that cannot be divided further (e.g., not composite

attributes (e.g., use last name & first name, not name) do not use derived attributes (attributes that can be calculated using other

attributes; e.g., age) use single value attributes not multi-valued (e.g., medication1, medication2,

etc.) multi-valued attributes, if they have their own important attributes should be

elevated to entities

e.g., attributes of the entity STUDENT might include name, address, etc.

STUDENT birth datefirst name

last namephotophone #

Identifier Each entity occurrence has a unique identifier The identifier is an attribute (or group of attributes)

that describes or identifies each entity occurrence An identifier should be unique to each occurrence Referred to as a ‘primary key’ in relational models

STUDENTe.g., in the list of potential attributes of the entity STUDENT, the identifier could be Student Number.

StudentID

Relationships

Association or connection between two or more entities Usually a verb HAS-A is also a common relationship

(EMPLOYEE-has a-DEPENDENT) E-R model also contains relationship classes

STUDENT takes COURSE

StudentID CourseID

Degree of Relationship: Binary

In a binary relationship, two entities are associated.This is the most common degree of relationship.

VACATIONER

takes

TRIP

EMPLOYEE

DEPARTMENT

works for

Degree of Relationship: Ternary

In a ternary relationship, three entities are associated

create

DESIGNER

WRITER ILLUSTRATOR

CUSTOMER

WAREHOUSE

ITEM

order

Degree of Relationship: Unary (Recursive)

In a recursive relationship, one entity is associated with itself

TEAM

plays

COURSE

requires

Child Toy

Employee Office

Musician Song

One-to-Many

One-to-One

Many-to-Many

1 M

M

1

N

1

Connectivity Connectivity describes constraints on relationship (also referred to as “maximum cardinality”) Number of instances of entity B that can (or must) be associated with each instance of entity A

rents

has

sings

Representing M:N binary relationships M:N relationships are represented by two 1:M relationships. the relationship is itself an entity, called a composite entity

(rectangle around the diamond) The composite entity often has its own attributes

STUDENT CLASSenrolls inM N

STUDENT CLASSenrolls inM M

Date Mark

1 1

Cardinality Cardinality is the specific number of entity occurrences

associated with one occurrence of the related entity often referred to as ‘business rules’ because cardinality is

usually determined by organizational policy

Child Toy1 M

e.g., at a toy lending library, a given child may not borrow any toys at all or borrow more than one (up to 3) toys. A toy may not be borrowed by anyone, or it may be borrowed by one child.

(0,3) (0,1)borrows

Occurrences DiagramPictorial mapping of the occurrences between two entities assists in understanding connectivity, cardinality

C1 T1

C2 T2

C3 T3

C4 T4

C5 T5

C6 T6A child may rent between 0 and 3 toys; a toy may only be rented by 0 or 1 child. One child may rent many toys (1:M)

Relationship Participation Also referred to as “minimum cardinality” Mandatory Participation

An instance of a given entity must definitely match an instance of a second entity

e.g., each student must enroll in exactly one course Optional Participation

An instance of a given entity does not necessarily participate in the relationship

lower bound of cardinality is zero e.g., a faculty member teaches zero, one, or two courses

makes1

MEMBER DONATION

OPTIONALMANDATORY

N

(0,N) (1,1)

a member may or may not make a donation but a donation must be associated with a member

From the CUSTOMER perspective:– a customer may make many orders (M orders of 1:M

connectivity)– a customer does not necessarily make orders (optional

participation of orders, cardinality is (0,N))

From the ORDER perspective:– an order is made by (associated with) one and only one

customer (1 customer of 1:M connectivity)– an order must be made by (associated with) a customer

(mandatory participation, cardinality is (1,1))

CUSTOMER ORDERmakes

1 M

(0,N) (1,1)

Example: Customers & Orders

Example: Customers & Orders

parent table

related table

common field