1. Chapter Three ( Relational Data Model) Objectives Introduction to Relational Data Models. Advantages of Relational Data Models. Restriction of Relational Data Model. Keys. What are a good BD Design?

2. 2 Relational Data Model: Developed by Codd in 1970. Conceptually simple. Based on mathematical set theory.

3. 3 Relational Data Model: Most important advantage of the RDBMS is its ability to hide the complexities of the relational model from the user.

4. Relational Database Models: Data are represented as a set of tables.

5. 5 Structure A set of tables ( Relations). Each relation has a unique name. Each relation has a set of attributes. Each relation has a set of tuples.

6. 6 Restriction on Relational DBMS No two tuples are the same. No two attributes are the same. Order of tuples are immaterial. Order of attributes are immaterial. Value of attributes must be atomic.

7. 7 Relational Database Example: Students Courses Faculty

8. Attributes of a Relation: Students (Name, ID, Major, Minor,….) Courses ( C_num, Dept, Cr, Description) Faculty (Name, ID, SSN, …..) 8

9. Tuples: Students (Name, ID, Major, Minor,….) _________________________________ John Smith1111, ITEC, VART Mary Smith2222, COSC, ITEC Lorry Joys4444, ACCT, COSC Courses (C_num, Dept, Cr, Description) _______________________________________ 345 ITEC 3 Databases I 445 ITEC 3 Databases II 9

10. 10 Keys: (Constraints) A set of attributes whose values uniquely identify each entity. Examples: Students (Name, ID, Major, Minor,….) Courses (C_num, Dept, Cr, Description) Faculty (Name, ID, SSN, …..)

11. 11 Keys: (Constraints) Primary key: 1- Uniqueness: At any given time, no two tuples can have the same value for a given primary key. 2-Minimally: None of the attributes in primary key can be discarded without distorting the uniqueness property 3-Selection: A key selected by the Database Administrator.

12. Primary key: Key’s role is based on determination If you know the value of attribute A, you can look up (determine) the value of attribute B. ID  GPA 12

13. 13 Keys Composite key Composed of more than one attribute. Key attribute Any attribute that is part of a key. Superkey Any combination of attributes that uniquely identifies each row. Candidate key

14. 14 Keys: (Constraints) Foreign key: An attribute(s) in an entity set (relation) which is the primary key of other entity set (relation) Example: Department(Name, Dept_Id, ….) Faculty(Name, Id, Dept_Id,…)

15. 15 Normal Forms (Guidelines for RD design) How do we know this is a good design? If it is not a good design, What should we do? Modify our design ??.

16. Normalization: Process for evaluating and correcting table structures to minimize data redundancies Reduces data anomalies Works through a series of stages called normal forms: First normal form (1NF) Second normal form (2NF) Third normal form (3NF) 16

17. Why Normalize Tables: Structure of data does not handle data very well The table structure appears to work; Report generated with ease Unfortunately, report may yield different results depending on what data anomaly has occurred 17

18. Each table represents a single subject No data item will be unnecessarily stored in more than one table All attributes in a table are dependent on the primary key 18

19. 19 Normal Forms (Guidelines for RD design) A relation is in 1NF if the values of domain is atomic for each attribute.

20. 20 First Normal Form: 1NF Example: Person (NameAgeChildren) Smith42John, Lori, Mark Person (NameAgeChildren) Smith42John Smith42Lori Smith42Mark

21. 21 First Normal Form: 1NF Example: Student (NameBirthday) S1Feb 2,91 S2March 8,88 Student (Name, D_Birth, M_Birth, Y_Birth) Note: 2NF and 3NF Deal with the relationship between non-key and key

22. First Normal Form: Repeating group Derives its name from the fact that a group of multiple entries of same type can exist for any single key attribute occurrence Relational table must not contain repeating groups Normalizing table structure will reduce data redundancies 22

23. 23 Second Normal Form: 2NF A relation is in 2NF if it is in 1NF and every attribute is Fully dependent on the entire key in this relation.

24. 24 Second Normal Form: 2NF Example: R(A,B,C,D) D partially depends on A,B C fully depends on A,B A&B are prime (part of key) If A is primary key. Is this in 2NF? If A&B is primary key. Is this in 2NF? A, B ---> C, D A ---> D

25. 25 Second Normal Form: 2NF What should we do with a relation which is not in 2NF? Example: R(A,B,C,D) A, B ---> C, D A ---> D R1 (A,B,C) R2(A,D)

26. 26 Second Normal Form: 2NF Example: R(PartWarehouseAddressQuantity P1W1Frostburg25 P2W1Frostburg30 P3W2Cumberland32 P4W4Frostburg25 P4W1 What is the primary key? Part, Warehouse ---> Quantity Warehouse ---> Address

27. 27 Second Normal Form: 2NF Problems: 1. Repetition of information: Changing the address W! 2. Unable to present information: Warehouse with no part So … R1 (Warehouse, Address) R2 (Part, Warehouse, Quantity)

28. 28 Second Normal Form: 2NF Example: R(Professor,Student,Course,Degree) P1S1C1Ph.D. P2S2C2M.S. P3S2C4M.S. P4S3C4Ph.D. Professor ---> Course Student ---> Degree Professor ---> Student Key? Not in 2NF R1(Student, Degree) R2(Professor, Course, Student)

29. 29  A relation is 3NF if it is in 2NF and every non-key attribute non transitively depends on the Primary Key. Example: R(A,B,C,D) A, B --->D D ---> C Fact: 3NF is violated when a non-key is a fact about another non-key Third Normal Form (3NF): R1(A,B,D) R2(D,C)

30. 30 Third Normal Form (3NF): Example: R(Employee, Dept, Location) Employee ---> Dept Dept ---> Location EmployeeDeptLocation E1D1Frostburg E2D2Frostburg E3D3Frostburg Problems? R1(Employee, Dept) R2(Dept, Location)

31. 31 Third Normal Form (3NF): Example: R(A,B,C,D) A,B ---> C A,C ---> D So A,B is the Primary Key Not in 3NF R1(A,B,C) R2(A,C,D)

32. 32 Null Values: No data entry Not permitted in primary key It is represent as: An unknown attribute value A known, but missing, attribute value A “not applicable” condition

33. 33 Controlled redundancy: Makes the relational database work Tables within the database share common attributes that enable the tables to be linked together Multiple occurrences of values in a table are not redundant when they are required to make the relationship work Redundancy exists only when there is unnecessary duplication of attribute values