Agenda for Week 1/31 & 2/2

Learn about database design Vocabulary Modeling tool: Entity relationship diagram

(ERD) Practical modeling concepts

Do database design Practice creating ERD’s Primarily from “draftsman” perspective

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Database Design

Goal for the database design section of the class: Be able to design a “good” database for a business application.

Objectives: Know how to read, understand, and create a

database model using a modeling tool - ERD’s.

Understand the three reasons we store data in a database.

Know the process of completing a database design.

Understand the structure and limitations of the relational model.

Know how to identify and differentiate the required components of a database design.

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What is database design?

Database design is the process of planning the structure or blueprint of stored data for an organization.

Process of database design

Can be understood from three different perspectives: Architect: Planning types of data necessary

to achieve the goals of the system. Engineer: Identifying detailed data

requirements and designing the structure of the data.

Draftsman: Creating a model to depict the data that will be stored in a database.

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Data design is documented with a data model

Most commonly used data modeling tool is an entity-relationship diagram (ERD).

An ERD contains: Entities. Attributes. Identifiers (primary key for each entity). Relationships. Cardinalities of the relationships. Foreign keys to support the relationships.

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All About Entities

Entities are nouns that describe the person, event, place, or thing about which we want to store data.

The name of an entity is singular, not plural. Examples: customer, book, order, invoice, employee, supplier.

An entity usually becomes a table in a database.

An entity instance is a single occurrence of an entity (a row in a table, or a record in a file).

Entities almost always have more than one entity instance. (Tables have more than one row – it is not common to create a table that has only one row.) For example, you might be interested in storing information

about the “chief financial officer” of an organization. If there is just one CFO, then you wouldn’t create an entity for CFO, you would create an entity for “employee” and figure out another way to store the fact that a specific employee is the CFO.

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Attributes

An attribute is a characteristic or property of an entity.

Synonyms include: Element, property or field.

Examples of attributes for an “employee” entity: Last name, First Name, Employee ID, Address,

City, State, Zip, Phone, Title, Starting employment date.

Attributes can be: Stored vs. derived. Simple or complex.

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Identifying Attributes (Identifiers)

An attribute that could uniquely identify an instance of an entity is called a “candidate key”. A candidate key that the analyst chooses to uniquely

identify an instance of an entity is called a “primary key”.

Primary keys are also referred to as identifiers.

Sometimes more than one attribute is needed to uniquely identify an instance of an entity. A group of attributes identifying an entity instance is

called a “concatenated key.” Synonyms for concatenated key are “composite key”

and “compound key”.

Primary keys

Each entity must have a primary key.

Two basic types of primary key: “Natural” primary key: primary key is created

from existing attribute or attributes. “Surrogate” primary key: primary key is a

“made up” attribute that has no function other than serving as a primary key.

For right now, we are going to try and use natural primary keys as much as possible.

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A bit about relationships

Entities do not usually exist in isolation.

A connecting line between two entities on an ERD represents a relationship.

A relationship can be depicted as a diamond or as a simple line.

A relationship is a natural business association existing between two or more entities.

A relationship creates a business rule.

A verb phrase describes the relationship.

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Cardinality of a relationship

Cardinality is a constraint on the number of entity instances that participate in a relationship.

Cardinality describes the minimum and maximum number of instances that one entity has with another entity in a relationship.

Cardinality also describes whether the relationship is mandatory or optional.

We use the crow’s foot notation to depict cardinality in our ERD’s in this class.

purchase order has item

man married_to woman

purchase order is_placed_with supplier

Examples: Binary relationship with explicit relationship symbol

man woman

purchase order supplier

is married to

is placed with

purchase order line item item

has contains

Examples: Binary relationship without explicit relationship symbol

employee

manages

Examples of Unary Relationships

inventory item

Person

Is married to

is part of

Employee Equipment

Assignment

Workspace

Isassigned

Is assigned

Isassigned

Example of a ternary relationship

location

patient

employee

test

treatmentvisit

Example of an n-ary relationship

Example of a context ERD

patient

treatment

employee

item

gets treatmentfrom

givestreatment to

provides atreatment for a

patient

has a

is had by

is provided by anemployee for a

patient

is managedby

is acomponent

of

location

isavailable

is usedfor

Context DataModel

Example of a logical ERD

Example of a Physical ERD

Patient

PK patientID

name address

Location

PK locationID

description address billing_code

PatientTreatment

PK patienttreatkey

date timeFK1 patientIDFK2 locationIDFK3 treatmentIDFK4 employeeID results

Treatment

PK treatmentID

insurance_code signup_dateFK1 itemID

Item

PK itemID

description

ItemComponent

PK ItemComponentKey

componentIDFK1 itemID quantity

Employee

PK employeeID

name office phoneFK1 mgrID

manages

has

Is delivered

at

Is given

by

Is of

usesIs

composed of

Strong entity

A strong entity is an entity that exists whether or not there is a relationship between it and another entity.

For example, you probably want to store data about employees, regardless of the fact that an employee provides services to a patient at a clinic.

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“Weak” or Associative Entities

An entity that does not exist unless it is linked to a strong entity.

For example, the patient treatment entity doesn’t exist unless a patient has a treatment.

On a logical ERD, a weak entity frequently borrows all or part of its primary key from another entity.

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Orderid

OrderDate

CustName

Itemid

ItemName Itemcost

Sellprice

Quantity

1234 08/30/2011 Jones A72 Martini Glasses – 4 pack 7.50 19.95 12

1234 08/30/2011 Jones A43 Tumbler, 12 oz – 8 pack 9.20 22.95 16

3900 08/26/2011 Smith A72 Martini Glasses – 4 pack 7.50 19.95 5

3900 08/26/2011 Smith B33 Ketchup Dispensers – 12 pack

8.70 25.95 22

3900 08/26/2011 Smith B97 Salt Shakers – 2 pack 2.20 9.95 3

8911 08/29/2011 Resco A43 Tumbler, 12 oz – 8 pack 9.20 22.95 35

8911 08/29/2011 Resco A72 Martini Glasses – 4 pack 7.50 19.95 235

Return to First Week Exercise Data (condensed)

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Need for Associative Entity

M:n relationship cannot be stored without data redundancy.

A m:n relationship usually has attributes that are part of the relationship. In the example below, you must decide where to store the quantity ordered for a given item on a given order.

Intersection entity is used to divide a m:n relationship.

Order

PK order_ID

order_date cust_name

Item

PK item_id

name item_cost sell_price

has

Is on

OrderID Order_date CustName

1234 08/30/2011 Jones

3900 08/26/2011 Smith

8911 08/29/2011 Resco

ItemID Name Itemcost

Sellprice

A72 Martini Glasses – 4 pack 7.50 19.95

A43 Tumbler, 12 oz – 8 pack 9.20 22.95

B33 Ketchup Dispensers – 12 pack 8.70 25.95

B97 Salt Shakers – 2 pack 2.20 9.95

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Possible Solution #1: Put the quantity ordered (qty_ordered) in the item entity, and create a concatenated primary key

OrderID Order_date CustName

1234 08/30/2011 Jones

3900 08/26/2011 Smith

8911 08/29/2011 Resco

OrderID ItemID Name Itemcost

Sellprice

Quantity

1234 A72 Martini Glasses – 4 pack 7.50 19.95 12

1234 A43 Tumbler, 12 oz – 8 pack 9.20 22.95 16

3900 A72 Martini Glasses – 4 pack 7.50 19.95 5

3900 B33 Ketchup Dispensers – 12 pack 8.70 25.95 22

3900 B97 Salt Shakers – 2 pack 2.20 9.95 3

8911 A43 Tumbler, 12 oz – 8 pack 9.20 22.95 35

8911 A72 Martini Glasses – 4 pack 7.50 19.95 235

Possible solution#1: Results in redundant data for item name, cost and sell price

Possible solution #2: Uses an intersection entity (Orderline) to avoid redundant data.

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OrderID Order_date CustName

1234 08/30/2011 Jones

3900 08/26/2011 Smith

8911 08/29/2011 Resco

ItemID Name Itemcost

Sellprice

A72 Martini Glasses – 4 pack 7.50 19.95

A43 Tumbler, 12 oz – 8 pack 9.20 22.95

B33 Ketchup Dispensers – 12 pack 8.70 25.95

B97 Salt Shakers – 2 pack 2.20 9.95

OrderID ItemID Qty_ordered

1234 A72 12

1234 A43 16

3900 A72 5

3900 B33 22

3900 B97 3

8911 A43 35

8911 A72 235

Possible Solution #2: Another table, but less data redundancy

Foreign Key

A way of supporting the relationship between two tables.

The primary key of one table is added to another table to link the two tables together.

In a 1:M relationship, the primary key of the entity on the “1” side of the relationship is added to the entity on the “M” side of the relationship.

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