Introduction to Data Modeling—Topics

IMS 6217: Introduction to Data Modeling

1Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Introduction to Data Modeling—Topics

• Introduction to Data Modeling

• Information elements

• Introduction to Entities, Attributes, and Relationships

• Basic notation

– Chen

– Alternative

• More on attributes

IMS 6217: Introduction to Data Modeling

2Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

What is Data Modeling?

• Data modeling is a step in the process that begins with the planning phase of Information Engineering and ends with construction of the physical database

InformationSystemsPlanning

InformationElements

EntitiesAttributesRelation-

shipsRules

PhysicalDatabase

Data Modeling

IMS 6217: Introduction to Data Modeling

3Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

What is Data Modeling (cont.)

• Data Modeling is a process of requirements identification, documentation, and revision that results in a finished DB design

– Process begins with gross identification of basic DB components

– Design is refined according to rules for storage and retrieval efficiency

• Finished DB design is converted to the physical DB

– Some DB design tools make the conversion automatically

IMS 6217: Introduction to Data Modeling

4Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Information Elements

• IS Design involves interviews with clients

– Clients don’t understand our terminology or DB concepts (or they wouldn’t need us!)

– We probably don’t understand much of theirs

– Examine forms, reports & filing cabinets

• Interviews & research will result in a collection of "Information Elements" (my term)

– Lists of items of concern to the client

– Items that crop up in interviews & research

– Items you recognize from your experience

IMS 6217: Introduction to Data Modeling

5Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Information Elements (cont.)

• Task is to determine which part of a data model the different information elements fit– Entity– Attribute– Relationship– Business rule– System input or output– None of the above (irrelevant)

IMS 6217: Introduction to Data Modeling

6Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Information Elements (cont.)

• Our determinations generate the base data model• Further analysis modifies and extends the data model

to its final form

– Add new entities as review of the business model reveals overlooked items

– Add many new entities as part of the normalization process

IMS 6217: Introduction to Data Modeling

7Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Entities

• "A person, place, object, thing, event, or concept about which the organization wishes to maintain data"

• Examples from the university's database might be STUDENT, CLASS, and PROFESSOR

• Each entity in the final data model will become a table in the physical database

• It is important to distinguish between entities and attributes of an entity

– Distinction may change with perspective

• We will also create new entities as we refine our data model

IMS 6217: Introduction to Data Modeling

8Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Occurrences

• "Occurrences" of an entity are individual instances of the entity

– You are an occurrence of the STUDENT entity

– I am an occurrence of the FACULTY entity

• Occurrences correspond to records in the database

• Take care not to confuse occurrences with entities

– Some authors use the term “Entity Set” to imply that the Entity is a collection of occurrences

IMS 6217: Introduction to Data Modeling

9Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Defining Entities

• It is amazingly important to explicitly define what is meant by each entity

• What is contained in the following entities?

– Customer − Order

– Sale − Employee

• Entity descriptions become part of the DB documentation (description property in SQL Server)

• You cannot assume that developers using the DB will have the save vision for the meaning of an entity that you do

IMS 6217: Introduction to Data Modeling

10Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Defining Entities (cont.)

• (One occurrence of this entity represents…) “A person or organization that has purchased products from the company or who has inquired about purchasing products” (Customer)

• … “A person that has signed an employment agreement with the company including former employees. Excludes applicants, contractors, and contractor employees” (Employee)

• Try very hard to avoid using the entity name as part of the definition.

• See lesson on Course Lessons Page

IMS 6217: Introduction to Data Modeling

11Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Attributes

• "A property or characteristic of an entity that is of interest to the organization"

• E.g., what characteristics of a STUDENT are of interest to the University?

– SSN, First Name, Last Name, Major, DOB, …

• What characteristics are not of interest?

• What about Professors and Classes?

• What about your project?

• Attributes become fields in a record in the physical database

IMS 6217: Introduction to Data Modeling

12Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Entities and Attributes

• There can be ambiguity—depending on perspective—in determining what should be an entity and what should be an attribute

– UCF may have an attribute of STUDENT that contains the high school each student graduated from

– The State of Florida Dept. of Education may consider high schools to be an entity with its own attributes

• Refinement of the database may require that some attributes be turned into new entities—watch for this as we continue in the course

IMS 6217: Introduction to Data Modeling

13Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Naming Entities and Attributes

• Balance brevity with completeness

• No Spaces

– Order Detail → OrderDetail or Order_Detail

• No SQL Reserved Words

– Order → CustomerOrder

– Date → OrderDate, HireDate, BirthDate

• My preference is for “Pascal Case”

– CustomerOrder

– LastInventoryDate

• Some organizations include data type indicator as an attribute prefix (e.g. smnySalesPrice)

IMS 6217: Introduction to Data Modeling

14Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Identifier Attributes (Primary Keys)

• Identifier Attribute: An attribute whose value uniquely identifies each occurrence of an entity

– SSN for student or faculty

– VIN for an automobile

– SKU for a retail product

• Composite Identifiers: More than one attribute is needed to uniquely identify an entity occurrence

– Dept Code & Number for a course

– Building Code & Room Number for a classroom

• Review Alternate Keys

IMS 6217: Introduction to Data Modeling

15Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Identifier Attributes (cont.)

• Identifier attributes define the entity as well as identifying occurrences

– What entity does VIN identify?

– What entity does State + TagNumber identify?

– SKU, SaleID, SKU + SaleID?

– SKU + StartDate?

– EmployeeID + SkillID?

– EmployeeID + PositionID + StartDate?

• Always check to ensure that the primary key is consistent with the entity name and the entity description

IMS 6217: Introduction to Data Modeling

16Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Documenting Identifier Attributes (cont.)

• Identifier attributes are underlined in an ER diagram(sometimes bold faced)

STUDENT

SSNLast

NameFirst

Name

SSNLastNameFirstName

STUDENT

DepartmentNumberName

CLASS

IMS 6217: Introduction to Data Modeling

17Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Relationships

• "A meaningful association between (or among) entities"

• What in the world does this mean?

• Relationships indicate how entities interact from the organization's perspective

• Relationships will end up defining paths through the database along which data will be retrieved

– The paths usually mirror real world associations between entities

IMS 6217: Introduction to Data Modeling

18Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Relationships (cont.)

• Relationships are verbs

– Buys, teaches, sells, owns, …

– Is a

– Has

• Relationship verb describes how two entities interact with each other

• If two entities do not interact (from the organization’s official viewpoint) then there is no relationship between them

– Professor ?? Football_Play

• ‘Direction’ of verb is not very important

Important special cases

IMS 6217: Introduction to Data Modeling

19Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Two Notation Schemes (Chen LDM)

STUDENT Takes CLASS

SSNLast

NameFirst

NameName

Entities are indicated by a box with the entity nameinside

Attributes are listed in ovalsattached to entities

Relationships are indicatedby diamonds

Relationships are connectedto entities by notation toindicate the cardinality ofthe relationship

IMS 6217: Introduction to Data Modeling

20Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Two Notation Schemes (Alternative LDM)

SSNLastNameFirstName

STUDENT

DepartmentNumberName

CLASSTakes

Entities shown as boxes

Entity name

Attributes

Relationship shown withoutthe diamond

IMS 6217: Introduction to Data Modeling

21Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Multivalued Attributes

• Multivalued Attributes are those that may have more than one value for the same entity occurrence

– EMPLOYEE Skill

– STUDENT Major

• Chen recommends illustrating with a double ellipse around the attribute

• We will see that multivalued attributes must be eliminated from the ER diagram

– I recommend dealing with this immediately (to be covered later)

– Don't model multivalued attributes

Value

STUDENT

Major

IMS 6217: Introduction to Data Modeling

22Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

Derived Attributes

• A derived attribute is one that can be calculated from other information in the database (data model)

– EMPLOYEE.Birthdate and Date give EMPLOYEE.Age

– Sum of all CUSTOMER.Purchases minus sum of all CUSTOMER.Payments gives CUSTOMER.Balance

• Derived attributes are shown with a dashed ellipse or the notation <d> in my modeling technique

• Later we will cover the decision on whether to implement derived attributes in the database

STUDENT

GPA

IMS 6217: Introduction to Data Modeling

23Dr. Lawrence West, MIS Department, University of Central FloridaLWEST@BUS.UCF.EDU

What's Next?

• More on relationships

– Attributes of relationships

– Degree of a relationship

– Cardinality of relationships