SECTION A – TRUE FALSE & MCQ 1. A key must be unique. 2. Ensuring that every value of a foreign key matches a value of the corresponding primary key is an example of a referential integrity constraint. 3. Every cell in a relation can hold only a single value. 4. In the relational model, each row of a table contains data that represents an attribute of the entity. 5. To be considered a composite key, a key must contain at least two attributes. 6. Candidate keys may or may not be unique. 7. The primary key is used both to identify unique rows in a relation and to represent rows in relationships. 8. Null values can cause problems because they are ambiguous. 9. When used to represent a relationship, the primary key must have the same name as the corresponding foreign key. 10. Every table is a relation, but not every relation is a table. 11. Every relation is a table, but not every table is a relation. 12. Which of the following terms is synonymous with "tuple"? A) Attribute B) Table C) Field D) Row E) Relation 13. Which of the following terms is synonymous with "relation"? A) Attribute B) Table C) Record D) Row E) Tuple 14. Which of the following is true about a key? A) It may be unique. B) It may be nonunique. C) It can only identify one row. D) Both A and B E) None of the above 15. A key that contains more than one attribute is called a(n) ________. A) composite key B) complex key C) multi-key D) n-key E) candidate key 16. A primary key is ________. A) not required to be unique B) used to represent columns in relationships C) a candidate key D) always automatically generated by the DBMS E) comprised of exactly one attribute 17. A candidate key is ________. A) never a primary key B) a combination of two or more attributes C) is always automatically generated by the DBMS D) a candidate to be the primary key E) None of the above 18. One or more entities can be associated together in relationships. 19. In a 1:1 relationship, a single entity instance of one type is related to a single entity instance of the same or another type. 20. Recursive relationships can be represented as 1:N or N:M, but not 1:1. 21. The subtype symbol is a circle with a line under it. 22. Unified Modeling Language (UML) has quickly replaced the E-R Model as the most popular technique for creating data models. 23. A PRODUCT entity instance is the collection of all PRODUCT entity classes. 24. An entity class is described by the structure of the entities in that class. 25. There is usually only one instance of an entity in an entity class. 26. The E-R Model assumes that all instances of a given entity class have the same attributes. 27. An entity identifier can be either unique or nonunique. 28. The number of entity classes involved in a relationship is the cardinality of the relationship. 29. It is possible for an entity to have a relationship to itself. 30. Maximum cardinality indicates whether or not an instance of one entity class must be related to at least one instance of another entity class. 31. One type of strong entity is the ID-dependent entity. 32. Subtype entities may be either exclusive or inclusive. 33. Changing aspects of a source document is much more difficult than changing the actual database, once constructed. 34. During the implementation phase of developing a database system, the data model is transformed into a database design. 35. When developing a database system, the database is constructed during the implementation phase. 36. During the design phase of developing a database system, the users are asked about the need for changes to existing forms and reports. 37. A use case is a description of the way a user will employ the features and functions of the new system. 38. Use cases can be used to validate the data model, design, and implementation. 39. In crow's foot E-R notation, the crow's foot indicates a maximum cardinality of one. 40. In crow's foot E-R notation, a circle indicates a minimum cardinality of zero. 41. In crow's foot E-R notation, the hash mark indicates both a minimum cardinality of one and a maximum cardinality of one. 42. In a traditional E-R diagram, the relationship is symbolized by a diamond. 43. A nonidentifying relationship exists between an ID-dependent entity and its parent. 44. The implementation step is a process that starts with the final system design as its input and produces a final system as its output. 45. An entity cannot be both weak and strong. SECTION B: ER MODELING You are required to create a conceptual data model of the data requirements for a company That specializes in IT training. The Company has 30 instructors and can handle up to 100 trainees per training session. The Company offers five advanced technology courses, each of which is taught by a teaching team of two or more instructors. Each instructor is assigned a maximum of two teaching teams or may be assigned to do research. Each trainee undertakes one advanced technology course per training session. (a) Identify the main entity types for the company. (b) Identify the main relationship types and specify the multiplicity for each relationship. State any assumptions you make about the data. (c) Using your answers for (a) and (b), draw a single ER diagram to represent the data requirements for the company. SECTION C: EER MODELING Highline University is a 4-year undergraduate school located in the Puget Sound region of Washington State.1 Highline University, like many colleges and universities in the Pacific Northwest, is accredited by the Northwest Commission on Colleges and Universities (NWCCU—see www.nwccu.org ). Like all the colleges and universities accredited by the NWCCU, Highline University must be reaccredited at approximately 5-year intervals. Additionally, the NWCCU requires annual status-update reports. Highline University is made up of five colleges: The College of Business, The College of Social Sciences and Humanities, the College of Performing Arts, the College of Sciences and Technology, and the College of Environmental Sciences. Jan Smathers is the president of Highland University, and Dennis Endersby is the provost (a provost is a vice president of academics; the deans of the colleges report to the provost). In this set of case questions, we will consider an information system for Highline University that will be used by Highline University’s Mentor Program. The Highline University Mentor Program recruit’s business professionals as mentors for Highline University students. The mentors are unpaid volunteers who work together with the students’ advisers to ensure that the students in the mentoring program learn needed and relevant management skills. In this case study, you will develop a data model for the Mentor Program Information System. Draw an E-R data model for the Highline University Mentor Program Information System 1 Highline University is a fictional university and should not be confused with Highline Community College located in Des Moines, Washington. Any resemblance between Highline University and Highline Community College is unintentional and purely coincidental. (MPIS). Use the IE Crow’s Foot E-R model for your E-R diagrams. Justify the decisions you make regarding minimum and maximum cardinalities. 1. Base on the case presented, create a separate entity for each scenario presented below. At Highline University, all students are required to live on campus and are assigned Highline University ID numbers and email accounts in the format FirstName.LastName@students.hu.edu. The student entity should track student last name, student first name, student University ID number, student email address, dorm name, dorm room number, and dorm phone number. At Highline University, all faculty advisers have on-campus offices and are assigned Highline University ID numbers and email accounts in the format FirstName.LastName@hu.edu. The faculty entity should track faculty last name, faculty first name, faculty University ID number, faculty email address, department, office building name, office building room number, and office phone number. Highline University alumni live off campus and were previously assigned Highline University ID numbers. Alumni have private email accounts in the format FirstName.LastName@somewhere.com. The alumni entity should track alumnus last name, alumnus first name, alumnus former-student number, email address, home address, home city, home state, home ZIP code, and phone number. Highline University mentors work for companies and use their company address, phone, and email address for contact information. They do not have Highline University ID numbers as mentors. Email addresses are in the format FirstName.LastName@companyname.edu. The mentor entity should track mentor last name, mentor first name, mentor email address, company name, company address, company city, company state, company ZIP code, and company phone number. 2. Create relationships between entities based on the following facts: Each student is assigned one and only one faculty adviser and must have an adviser. One faculty member may advise several students, but faculty members are not required to advise students. Only the fact of this assignment is to be recorded in the data model—not possible related data (such as the date the adviser was assigned to the student). Each student may be assigned one and only one mentor, but students are not required to have a mentor. One mentor may mentor several students, and a person may be listed as a mentor before he or she is actually assigned students to mentor. Only the fact of this assignment is to be recorded in the data model—not possible related data (such as the date the mentor was assigned to the student). B. Each mentor is assigned to work and coordinate with one and only one faculty member, and each mentor must work with a faculty member. One faculty member may work with several mentors, but faculty members are not required to work with mentors. Only the fact of this assignment is to be recorded in the data model—not possible related data (such as the date the faculty member was assigned to the mentor). Each mentor may be an alumnus, but mentors are not required to be alumni. Alumni cannot, of course, be required to become mentors. Revise the E-R data model you created in part A to create a new E-R data model based on the fact that students, faculty, alumni, and mentors are all a PERSON. Use the IE Crow’s Foot E-R model for your E-R diagrams. Justify the decisions you make regarding minimum and maximum cardinalities. Note that while the following business rules need to be implemented in your design, the E-R model notation may not be able to express them, in which case you will need to add text notes to your diagram indicating which rules will be to be enforced in SQL structures or application code (alternatively, write a memo to accompany your E-R diagram that contains these notes). The relevant business rules are: A person may be a current student, an alumnus, or both, because Highline University does have alumni return for further study. A person may be a faculty member or a mentor, but not both. A person may be a faculty member and an alumnus. A person may be a mentor and an alumnus. A current student cannot be a mentor. Each mentor may be an alumnus, but mentors are not required to be alumni. Alumni cannot, of course, be required to become mentors. C. Extend and modify the E-R data model you created in part B to allow more data to be recorded in the MPIS system. Use the IE Crow’s Foot E-R model for your E-R diagrams. Justify the decisions you make regarding minimum and maximum cardinalities. The MPIS needs to record: The date a student enrolled at Highline University, the date the student graduated, and the degree the student received The date an adviser was assigned to a student and the date the assignment ended The date an adviser was assigned to work with a mentor and the date the assignment ended The date a mentor was assigned to a student and the date the assignment ended D. Write a short discussion of the difference between the three data models you have created. How does data model B differ from data model A, and how does data model C differ from data model B? What additional features of the E-R data model were introduced when you created data models B and C?
