1. ER Modeling Exercise
Consider a set of courses, both at grad and undergrad level. Each course has at least one section. Each section is taught by only one instructor (who can teach more than one section). Students (grads and undergrads), who may also be instructors for other courses, may attend only one section of (possibly several) courses in their respective level (instructors may attend any courses). Each student will have a mark for the courses taken, which will have an average mark of their own. Courses may not be offered every term. Feel free to add attributes as you wish (keys are necessary though).

2. ER Modeling Exercise
Consider a set of courses, both at grad and undergrad level. Each course has at least one section. Each section is taught by only one instructor (who can teach more than one section). Students (grads and undergrads), who may also be instructors for other courses, may attend only one section of (possibly) several courses in their respective level (instructors may attend any courses). Each student will have a mark for the courses taken, which will have an average mark of their own. Courses may not be offered every term.

3. ER Modeling Exercise
Consider a set of courses, both at grad and undergrad level. Each course has at least one section. Each section is taught by only one instructor (who can teach more than one section). Students (grads and undergrads), who may also be instructors for other courses, may attend only one section of (possibly) several courses in their respective level (instructors may attend any courses). Each student will have a mark for the courses taken, which will have an average mark of their own. Courses may not be offered every term.

4. ER Modeling Exercise
Consider a set of courses, both at grad and undergrad level. Each course has at least one section. Each section is taught by only one instructor (who can teach more than one section). Students (grads and undergrads), who may also be instructors for other courses, may attend only one section of (possibly) several courses in their respective level (instructors may attend any courses). Each student will have a mark for the courses taken, which will have an average mark of their own. Courses may not be offered every term.

5. ER Modeling Exercise
Consider a set of courses, both at grad and undergrad level. Each course has at least one section. Each section is taught by only one instructor (who can teach more than one section). Students (grads and undergrads), who may also be instructors for other courses, may attend only one section of (possibly) several courses in their respective level (instructors may attend any courses). Each student will have a mark for the courses taken, which will have an average mark of their own. Courses may not be offered every term.

6. ER Modeling Exercise
Consider a set of courses, both at grad and undergrad level. Each course has at least one section. Each section is taught by only one instructor (who can teach more than one section). Students (grads and undergrads), who may also be instructors for other courses, may attend only one section of (possibly several) courses in their respective level (instructors may attend any courses). Each student will have a mark for the courses taken, which will have an average mark of their own. Courses may not be offered every term.

7. Relational Databases Basic concepts Advantages Industry standard
Data model: organize data as tables
A relational database is a set of tables
Advantages
Simple concepts
Solid mathematical foundation
set theory
Powerful query languages
Efficient query optimization strategies
Design theory
Industry standard
Relational model
SQL language

8. Relational Model Relation Tabular structure of data where
A relation R with attributes A={A1, A2, …, An} defined over n domains D={D1, D2, ..., Dn} (not necessarily distinct) is a time varying set of n-tuples <d1, d2, ..., dn> such that d1D1d2D2dnDnandA1D1A2D2 AnDn
Tabular structure of data where
R is the table heading
attributes are table columns
each tuple is a row

9. Relation Schemes and Instances
Relational scheme
A relation scheme is the definition; i.e., a set of attributes
A relational database scheme is a set of relation schemes:
i.e., a set of sets of attributes
Relation instance (simply relation)
A relation is an instance of a relation scheme
a relation r over a relation scheme R = {A1, ..., An} is a subset of the Cartesian product of the domains of all attributes, i.e.,
r  D(A1) D(A2) …  D(An)

10. Domains A domain is a set of acceptable values for a variable.
Example :
Names (strings with no numbers), Salary ranges
Simple/Composite domains
Address = Street name+street number+city+province+ postal code
Domain compatibility
Binary operations (e.g., comparison to one another, addition, etc) can be performed on them.
Full support for domains is not provided in many current relational DBMSs

11. Relation Schemes Underlined attributes are relation keys. Tabular form
EMP(ENO, ENAME, TITLE, SAL)
PROJ (PNO, PNAME, BUDGET)
WORKS(ENO,PNO, RESP, DUR)
Underlined attributes are relation keys.
Tabular form
EMP
ENO
ENAME
TITLE
SAL
PROJ
PNO
PNAME
BUDGET
WORKS
ENO
PNO
RESP
DUR

12. Example Relation Instances
EMP
WORKS
ENO
ENAME
TITLE
ENO
PNO
RESP
DUR E1
J. Doe
Elect. Eng. E1 P1
Manager 12 E2
M. Smith
Syst. Anal. E2 P1
Analyst 24 E3
A. Lee
Mech. Eng. E2 P2
Analyst 6 E4
J. Miller
Programmer E3 P3
Consultant 10 E5
B. Casey
Syst. Anal. E3 P4
Engineer 48 E6
L. Chu
Elect. Eng. E4 P2
Programmer 18 E7
R. Davis
Mech. Eng. E5 P2
Manager 24 E6 P4
Manager 48 E8
J. Jones
Syst. Anal. E7 P3
Engineer 36 E7 P5
Engineer 23 E8 P3
Manager 40
PROJ
PNO
PNAME
BUDGET P1
Instrumentation
150000 P2
Database Develop.
135000 P3
CAD/CAM
250000 P4
Maintenance
310000 P5
CAD/CAM
500000

13. Properties Based on the set theory All attribute values are atomic
no ordering among attributes and tuples
no duplicate tuples allowed
value-oriented: tuples are identified by the attributes values
All attribute values are atomic
no repeating groups
Degree
number of attributes
Cardinality
number of tuples

14. Integrity Constraints
Key Constraints
Key: a set of attributes that uniquely identifies tuples
Candidate key: a minimum set of attributes that form a key
Primary key: a designated candidate key
Data Constraints
Functional dependency, multivalued dependency, join dependency
check constraints
Others
Null constraints
Referential constraints