1. BIS 360 – Lecture Eight Ch. 12: Database Design and Normalization

2. Objectives Where are we? ER Diagram Transformation Why DB Normalization? Database Anomalies Normalization Theory 1NF - 3NF

3. Where we are now Project ID and Selection Project Initiation & Planning Analysis Logical Design Physical Design Implementation Maintenance 1. Database Design (Ch. 12) 2. Form and Report Design (Ch. 13) 3. Interface Design (Ch. 14)

4. Why we design a database E-R ModelDFD Model  Information Database  Applications  Reports Bills Charts...

5. DB Design – Where we start From the Conceptual Data Model (ERD) examine the diagram for accuracy – entities, attributes,relationships, and cardinalities Transform this Conceptual Data Model into Logical Data Model (i.e., Relational Data Model) a set of flat tables (relations)

6. ER Diagram Transformation Step 1: For each regular entity type E, create a relation R that includes all the simple attributes. A unique identifier of E will be a primary key of R EMPLOYEE EmpIDEmpLNameEmpFNameSalary PK: EmpID E R

7. ER Diagram Transformation Step 2: For each weak entity type W with identifying entity type E, create a relation Rw with all the attributes of W and also create a relation Re for E as explained in Step 1. Then, include the primary key of Re as a foreign key of Rw. A combination of the partial identifier of W and the unique identifier of E will be a primary key of Rw. EMPLOYEE EmpIDEmpLNameEmpFNameSalary PK: EmpID DEPENDENT EW DpdSSNDpdLNameDpdFNameEmpID PK: EmpID + DpdSSN FK: EmpID Re Rw

8. ER Diagram Transformation Step 3: When there is a 1:1 relationship between entity type S and T, create relations Rs and Rt as explained in step 1. Include a primary key of S as a foreign key of T. EMPLOYEE EmpIDEmpLNameEmpFNameSalary PK: EmpID DEPARTMENT ST DeptIDDeptNameDeptPhoneEmpID PK: DeptID FK: EmpID Rs Rt manages is managed by

9. ER Diagram Transformation Step 4: When there is a 1:M relationship between entity types S and T, create relations Rs and Rt as explained in step 1. If T is an entity type at the MANY-side, include a primary key of Rs as a foreign key of Rt. DEPARTMENT DeptIDDeptNameDeptPhone PK: DeptID EMPLOYEE ST EmpIDEmpLNameEmpFNameSalaryDeptID PK: EmpID FK: DeptID Rs Rt works for hires

10. ER Diagram Transformation Step 5: When there is a M:N relationship P between entity types S and T and there is no property associated with this relationship P, create relations Rs and Rt as explained in step 1. Also create a relation Rp to represent the relationship and include primary keys of Rs and Rt as foreign keys of Rp. A combination of primary keys of Rs and Rt will be a primary key of Rp. WhIDWhName PK: WhID WAREHOUSEPRODUCT ST WhIDProdID PK: WhID + ProdID FK: WhID, ProdID Rs Rp ProdIDProdNameProdPrice Rt PK: ProdID

11. ER Diagram Transformation Step 6: When there is a M:N relationship P between entity types S and T and there are some properties associated with this relationship P, create relations Rs, Rt, and Rp as explained in step 5. All properties associated with the relationship P will be the non-key attributes of Rp. SchID STUDENT SCHOOL SSN Name Phone ZIP Name Type ZIP Attends Date STUDENT ( SSN, Name, Phone, Zip ) SCHOOL ( SchID, Name, Type, Zip ) STU_SCH ( SSN, SchID, Date, Degree ) Degree

12. Complex ERD Transformation Example of (M:N) Relationship ORDER ( CID, ProdID, Date, Units ) Same customer may order same product many times Q: Are you happy with the above design? ProdID CUSTOMER PRODUCT CID Name Phone ZIP...... Desc. U_Price Qty...... Order Date Units

13. Complex ERD Transformation Example of (M:N) Relationship ORDER ( OrderID, CID, ProdID, Date, Units ) Same customer may order same product many times ProdID CUSTOMER PRODUCT CID Name Phone ZIP...... Desc. U_Price Qty...... Order Date Units Create a unique primary key – OrderID

14. Why DB Normalization? To avoid database processing errors (anomalies) To verify the relations derived from the ER diagram – each derived relation would be at least in 3rd normal form (3NF)

15. Database Anomalies Anomalies -- Data errors occurred during or after the processing of data Three types of anomalies Insertion anomaly - the difficulty in adding new data due to the poor design of a relation Deletion Anomaly - unintentional data loss due to the deletion of some data Update Anomaly - data become inconsistent after some data were updated

16. Insertion Anomaly EmpIDDeptNameProjectBudgetLocation 1MktJohnA100000MI 1MktJohnB200000IN 2EngJimA100000MI 3AcctJoeC350000IL EMPLOYEE-PROJECT EmpIDDeptNameProjectBudgetLocation 1MktJohnA100000MI 1MktJohnB200000IN 2EngJimA100000MI 3AcctJoeC350000IL 4FinJackA100000MI 4FinJackC350000IL 5HRJunenull !!null Insert new employees

17. Insertion Anomaly EmpIDDeptNameProjectBudgetLocation 1MktJohnA100000MI 1MktJohnB200000IN 2EngJimA100000MI 3AcctJoeC350000IL EMPLOYEE-PROJECT EmpIDDeptNameProjectBudgetLocation 1MktJohnA100000MI 1MktJohnB200000IN 2EngJimA100000MI 3AcctJoeC350000IL 1MktJohnD250000MN 2EngJimD250000MN null !!null E400000WI Insert new projects

18. Deletion Anomaly EmpIDDeptNameProjectBudgetLocation 1MktJohnA100000MI 1MktJohnB200000IN 2EngJimA100000MI 3AcctJoeC350000IL EMPLOYEE-PROJECT EmpIDDeptNameProjectBudgetLocation 2EngJimA100000MI 3AcctJoeC350000IL Delete employee # 1 EmpIDDeptNameProjectBudgetLocation 1MktJohnB200000IN 3AcctJoeC350000IL Delete project A

19. Update Anomaly EmpIDDeptNameProjectBudgetLocation 1MktJohnA100000MI 1MktJohnB200000IN 2EngJimA100000MI 3AcctJoeC350000IL EMPLOYEE-PROJECT EmpIDDeptNameProjectBudgetLocation 1FinJohnA100000MI 1FinJohnB200000IN 2EngJimA100000MI 3AcctJoeC350000IL Update employees # 1

20. Normalization Theory Basic Concept - Functional Dependency Functional Dependency (FD): A relationship between attributes of an entity. FD is the foundation of Normalization. Notation: a  b - v alue of a uniquely determines the value of b  a is a “determinant”  a functionally determines b  b is functionally dependent on a

21. Normalization Theory Functional Dependency - Examples Interpretation: either SSN or EmpID can uniquely determine his/her Name, Phone, and DOB, but not the reverse! Both SSN and EmpID are candidate keys You can choose one of them as a PK SSN NamePhoneDOB EmpID EMPLOYEE ( SSN, EmpID, Name, Phone, DOB ) or EMPLOYEE ( SSN, EmpID, Name, Phone, DOB )

22. Normalization Theory Functional Dependency - Examples VIN # of doors ColorType Interpretation: VIN can uniquely determine a vehicle’s # of doors, Color, and Type, but not the reverse! VEHICLE ( VIN, # of doors, Color, Type ) VIN is the only candidate key and it is used as a PK

23. Database Normalization Where is the beef? Reality is not that simple ! All candidate keys, including PK, are the determinant But, determinant may not be the candidate key Q: What is the difference between a candidate key and a determinant? A: They are similar, but not the same - Scope

24. Database Normalization Where is the beef? Call # is a candidate key and is used as a PK Call # is also a determinant of CourseID, Title, and Classroom CourseID is a determinant of Title Q: Should we put these four attributes on the same table (relation)? A: No !! We need database normalization Title Call # ClassroomCourseID

25. Database Normalization Basic Ideas Unnormalized 1st NF (1NF) 2nd NF (2NF) 3rd NF (3NF)

26. Database Normalization Normal Form Definitions A relation is in its first normal form (1NF) if it does not contain repeating groups. A relation is in its second normal form (2NF) if every non-primary key attribute is fully dependent on the (whole) primary key. A relation is in its third normal form (3NF) if it has no transitive dependency between non-key attributes.

27. First Normal Form (1NF) 1NF: A relation is in its first normal form (1NF) if it does not contain repeating groups Phone SIDNameSexDOBPhone Major Repeating groups Normalization STUDENT ( SID, Name, Sex, DOB ) STU_PHONE ( SID, Phone ) STU_MAJOR ( SID, Major )

28. Second Normal Form (2NF) 2NF: A relation is in its second normal form (2NF) if it is in 1NF and every non- primary key attribute is fully functionally dependent on the (whole) primary key 123, Jim, Line crew, 01/01/96, Factory 123, Jim, Supervisor, 01/01/99, Factory 211, John, Sales Rep, 09/01/94, MKT 211, John, Sales Manager, 01/01/98, MKT 235, Joe, Accountant, 07/01/96, Acct A combination of EmpID and SDate is the only candidate key and is used as a PK (EmpID, SDate)  Name, Position, Dept EmpID  Name, Dept Q: Do we see any partially functional dependency? JOB_HIST ( EmpID, Name, Position, SDate, Dept )

29. Second Normal Form (2NF) JOB_HIST ( EmpID, Name, Position, SDate, Dept ) Normalization JOB_HIST ( EmpID, SDate, Position ) EMPLOYEE ( EmpID, Name, Dept )

30. Comments on 2NF Verification You don’t need to worry about whether a relation is in its 2NF if its PK includes only one attribute (Why?) Because Partially functional dependency only occurs when the PK is a composite (compound) key

31. Third Normal Form (3NF) 3NF: A relation is in its third normal form (3NF) if it is in 2NF and there is no transitive dependency between non-key attributes in the relation Transitive dependency: If a  b, and b  c, then there is a transitive dependency between a and c EmpID  Name, Phone, Office, Street, City, State, Zip Phone  Office Zip  City, State Q: Do you see the transitive dependency? EMPLOYEE ( EmpID, Name, Phone, Office, Street, City, State, Zip )

32. Third Normal Form (3NF) EMPLOYEE ( EmpID, Name, Phone, Office, Street, City, State, Zip ) Normalization EMPLOYEE ( EmpID, Name, Phone, Street, Zip ) PHONE ( Phone, Office ) ZIP ( Zip, City, State )