Introduction to Data Modeling—Topics
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Transcript of Introduction to Data Modeling—Topics
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IMS 6217: Introduction to Data Modeling
1Dr. Lawrence West, MIS Department, University of Central [email protected]
Introduction to Data Modeling—Topics
• Introduction to Data Modeling
• Information elements
• Introduction to Entities, Attributes, and Relationships
• Basic notation
– Chen
– Alternative
• More on attributes
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IMS 6217: Introduction to Data Modeling
2Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
3Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
4Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
5Dr. Lawrence West, MIS Department, University of Central [email protected]
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)
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IMS 6217: Introduction to Data Modeling
6Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
7Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
8Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
9Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
10Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
11Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
12Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
13Dr. Lawrence West, MIS Department, University of Central [email protected]
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)
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IMS 6217: Introduction to Data Modeling
14Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
15Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
16Dr. Lawrence West, MIS Department, University of Central [email protected]
Documenting Identifier Attributes (cont.)
• Identifier attributes are underlined in an ER diagram(sometimes bold faced)
STUDENT
SSNLast
NameFirst
Name
SSNLastNameFirstName
STUDENT
DepartmentNumberName
CLASS
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IMS 6217: Introduction to Data Modeling
17Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
18Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
19Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
20Dr. Lawrence West, MIS Department, University of Central [email protected]
Two Notation Schemes (Alternative LDM)
SSNLastNameFirstName
STUDENT
DepartmentNumberName
CLASSTakes
Entities shown as boxes
Entity name
Attributes
Relationship shown withoutthe diamond
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IMS 6217: Introduction to Data Modeling
21Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
22Dr. Lawrence West, MIS Department, University of Central [email protected]
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
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IMS 6217: Introduction to Data Modeling
23Dr. Lawrence West, MIS Department, University of Central [email protected]
What's Next?
• More on relationships
– Attributes of relationships
– Degree of a relationship
– Cardinality of relationships