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Data Entity, Attribute, and Relationship: ER Modeling Challenges in a Student Registration System

This article discusses the challenges in identifying entities, attributes, and relationships in an ER model for a student registration system.

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Data Entity, Attribute, and Relationship: ER Modeling Challenges in a Student Registration System

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  1. Entity, Attribute, and Relationship • DATA ENTITY TYPE: a noun, i.e. roles, events, locations, people, tangible things about which we wish to maintain data • ATTRIBUTE: noun, data elements that describe characteristics of the entity type • RELATIONSHIP: verb phrase, an association between entities of interest to the organization • Labels of the dataflows in DFD's correspond to entities and attributes in the ERD.

  2. ER Modeling Challenges Identifying entities and attributes in a syetem Entity: Student • Attributes of the Entity • Student Name • Social Security No. (Key) • Major • Mailbox Number • Permanent Address • Street • City • State • Zip • Credit Hours Earned

  3. Which of the following would be potential entities in a system forstudent registration? • Student • Registrar • Course number • Room • Class • Course • Pre-requisites • Name • Junior • Sophomore • Jane Stevens • MIS 321 01 • Instructor • Password/pin • Bill

  4. Potential entities in a system for student registration . . . • Entity Types: student, course, and depending on scope bill, instructor • Attributes of Entity: course number, room, class standing, pre-requisites, name, password/pin, and depending on scope (instructor) • Possible Attribute Values: junior, sophomore • Instances: Jane Stevens, MIS 321 01

  5. Types of attributes • Composite attributes • Attributes with subattributes • Address: street address, city, state, zip. • Single valued • Attribute with only one value • Age of a person, sudent id • Multivalued • Attribute with more than one value • Tel-phone numbers • Stored and derived attribute • Strongly related • One is derived from other (stored attribute). • Age of a person can be derived from the attribute birth date. • Null value • Attribute with no value • Apartment number in a streetaddress can have the value null for an address which is not in an appartment

  6. Criteria for Selecting Primary Key • The value will not change over the life of each instance of the entity • For each instance of the entity, you are guaranteed to have a value for the attribute • Avoid “intelligent keys” -- a key whose structure indicates classification or location -- these often change • Single attribute keys are easier to work with than large multi-attribute composite keys • Create a separate surrogate key

  7. What would be a good primary key choice for the following entity? ENTITY: Course • Course Number • Quarter Offered • Instructor • Course Description • Time Offered • Day Offered

  8. ID number ENTITY: VIDEO • Movie Title , Length , Copy Number , Awards , Lead Actors/Actresses , Availability (logical) • Movie Title? • Movie Title and Copy No.? • How to distinguish between a remake and original with the same title? • May need to create an attribute that is unique -- video id number

  9. Weak Entity Types • Existence depends on the relation with another entity • No key attribute • Identified by own attributes in combination with the attributes of the entity on which it depends on. • A weak entity cannot exist without the relation it has with the entity it is related.

  10. Symbols in an ERD

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