1. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-1 COS 346 Day 8

2. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-2 Agenda Questions? Assignment Two Corrected –1 A, No B’s, 5 C’s, 3 D’s –We will cover the assignment in class Assignment 3 posted –Due Feb 16 –Use VISIO http://www.utexas.edu/courses/mis325/tutorial/visio/visio.htm http://www.utexas.edu/courses/mis325/tutorial/visio/visio.htm Assignment 4 will be posted next Class AMD WILL Due Feb 23 Start Thinking about a Capstone Project –Must be a database project Quiz 1 –Feb 23 –DP Chap 1-6, SQL Chap 1 & 2 –20 M/C and 5 Short Essay Transforming Data Models into Database Designs

3. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-3 Assignment 2 Explain the conditions under which each of the following are true: 1.Phone  (FirstName, LastName) 2.(Phone, FirstName)  LastName 3.(Phone, LastName)  FirstName 4.(LastName, FirstName)  Phone 5.Phone  LastName 6.Phone  FirstName 7.Phone  (FirstName, LastName) Is condition 7 the same as conditions 5 and 6? Why or why not?

4. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-4 Assignment 2 Consider the tables: CUSTOMER (Phone, FirstName, LastName) ORDER (OrderNumber, DateIn, DateOut, Phone) State an appropriate referential integrity constraint. Consider the tables: CUSTOMER (Phone, FirstName, LastName) ORDER (OrderNumber, DateIn, DateOut, FirstName, LastName) What does the following referential integrity constraint mean? ORDER (FirstName, LastName) must be in CUSTOMER (FirstName, LastName) Is this constraint the same as: ORDER (FirstName) must be in CUSTOMER (FirstName) and ORDER. (LastName) must be in CUSTOMER (LastName) Explain why or why not.

5. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-5 Assignment 2 Do you prefer the design in B or the design in C? Explain your reasoning B. CUSTOMER (Phone, FirstName, LastName) ORDER (OrderNumber, DateIn, DateOut, Phone) C CUSTOMER (Phone, FirstName, LastName) ORDER (OrderNumber, DateIn, DateOut, FirstName, LastName) Transform the following table into two or more tables in BCNF and 4NF. Indicate the primary keys, candidate keys, foreign keys, and referential integrity constraints. Make and state assumptions as necessary. ORDER (CustomerNumber, FirstName, LastName, Phone, OrderNumber, DateIn, DateOut, ItemType, Quantity, ItemPrice, ExtendedPrice, SpecialInstructions)

6. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-6 Assignment 2 Explain how your answer to question E changes depending on whether you assume CustomerNumber  (FirstName, LastName) or CustomerNumber  (FirstName, LastName)

7. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-7 David M. Kroenke’s Chapter Six: Transforming Data Models into Database Designs Part One Database Processing: Fundamentals, Design, and Implementation

8. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-8 Steps for Transforming a Data Model into a Database Design

9. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-9 Create a Table for Each Entity EMPLOYEE (EmployeeNumber, EmployeeName, Phone, Email, HireDate, ReviewDate, EmpCode) Note shadowless table Primary key is designated by key symbol

10. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-10 Select the Primary Key The ideal primary key is short, numeric and fixed Surrogate keys meet the ideal, but have no meaning to users

11. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-11 Specify Candidate (Alternate) Keys The terms candidate key and alternate key are synonymous Candidate keys are alternate identifiers of unique rows in a table ERwin uses AKn.m notation, where n is the number of the alternate key, and m is the column number in that alternate key

12. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-12 Specify Candidate (Alternate) Keys

13. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-13 Specify Column Properties: Null Status Null status indicates whether or not the value of the column can be NULL

14. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-14 Specify Column Properties: Data Type Generic Data Types: –CHAR(n) –VARCHAR(n) –DATE –TIME –MONEY –INTEGER –DECIMAL

15. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-15 Specify Column Properties: SQL Server Data Types

16. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-16 Specify Column Properties: Oracle Data Types

17. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-17 Specify Column Properties: Default Value A default value is the value supplied by the DBMS when a new row is created

18. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-18 Specify Column Properties: Data Constraints Data constraints are limitations on data values: –Domain constraint - Column values must be in a given set of specific values –Range constraint - Column values must be within a given range of values –Intrarelation constraint – Column values are limited by comparison to values in other columns in the same table –Interrelation constraint - Column values are limited by comparison to values in other columns in other tables [Referential integrity constraints on foreign keys]

19. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-19 Verify Normalization The tables should be normalized based on the data model Verify that all tables are: –BCNF –4NF

20. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-20 Create Relationships: 1:1 Strong Entity Relationships Place the key of one entity in the other entity as a foreign key: –Either design will work – no parent, no child –Minimum cardinality considerations may be important: O-M will require a different design that M-O, and One design will be very preferable

21. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-21 Create Relationships: 1:1 Strong Entity Relationships

22. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-22 Create Relationships: 1:N Strong Entity Relationships Place the primary key of the table on the one side of the relationship into the table on the many side of the relationship as the foreign key The one side is the parent table and the many side is the child table, so “Place the key of the parent in the child”

23. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-23 Create Relationships: 1:N Strong Entity Relationships

24. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-24 Create Relationships: N:M Strong Entity Relationships In an N:M strong entity relationship there is no place for the foreign key in either table: –A COMPANY may supply many PARTs –A PART may be supplied by many COMPANYs

25. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-25 Create Relationships: N:M Strong Entity Relationships The solution is to create an intersection table that stores data about the corresponding rows from each entity The intersection table consists only of the primary keys of each table which form a composite primary key Each table’s primary key becomes a foreign key linking back to that table COMPANY_PART_INT (CompanyName, PartNumber)

26. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-26 Create Relationships: N:M Strong Entity Relationships COMPANY_PART_INT (CompanyName, PartNumber)

27. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-27 David M. Kroenke’s Database Processing Fundamentals, Design, and Implementation (10 th Edition) End of Presentation: Chapter Six Part One

28. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-28 COS 346 Day 9

29. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-29 Agenda Questions? Assignment 3 posted –Due Today Assignment 4 is posted –Due Feb 23 Start Thinking about a Capstone Project –Must be a database project Quiz 1 –Feb 23 –DP Chap 1-6, SQL Chap 1 & 2 –20 M/C and 5 Short Essay Transforming Data Models into Database Designs

30. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-30 David M. Kroenke’s Chapter Six: Transforming Data Models into Database Designs Part Two Database Processing: Fundamentals, Design, and Implementation

31. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-31 Relationships Using ID-Dependent Entities: Four Uses for ID-Dependent Entities Representing N:M Relationships –We just discussed this Association Relationships Multivalued Attributes Archtype/Instance Relationships

32. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-32 Relationships Using ID-Dependent Entities: Association Relationships An intersection table: –Holds the relationships between two strong entities in an N:M relationship –Contains only the primary keys of the two entities: As a composite primary key As foreign keys An association table: –Has all the characteristics of an intersection table –PLUS it has one or more columns of attributes specific to the associations of the other two entities

33. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-33 Relationships Using ID-Dependent Entities: Association Relationships QUOTATION (CompanyName, PartNumber, Price)

34. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-34 Relationships Using ID-Dependent Entities: Multivalued Attributes As a data model As a set of tables

35. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-35 Relationships Using ID-Dependent Entities: Archetype/Instance Pattern As a data model As a set of tables

36. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-36 Relationships Using Weak Entities: Archetype/Instance Pattern As a data model As a set of tables

37. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-37 Mixed Entity Relationships: The Line-Item Pattern As a data model

38. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-38 Mixed Entity Relationships: The Line-Item Pattern As a set of tables

39. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-39 Mixed-Entity Relationships As a data model As a set of tables

40. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-40 Subtype Relationships As a data model As a set of tables

41. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-41 Recursive Relationships: 1:1 Recursive Relationships As a data model As a table

42. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-42 Recursive Relationships: 1:N Recursive Relationships As a data model As a table

43. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-43 Recursive Relationships: N:M Recursive Relationships As a data model As a set of tables

44. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-44 Representing Ternary and Higher- Order Relationships Ternary and higher-order relationships may be constrained by the binary relationship that comprise them: –MUST constraint - Requires that one entity must be combined with another entity in the ternary (or higher- order) relationship –MUST NOT constraint - Requires that certain combinations of two entities are not allowed to occur in the ternary (or higher-order) relationship –MUST COVER constraint – A binary relationship specifies all combinations of two entities that must appear in the ternary (or higher-order) relationship

45. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-45 MUST Constraint

46. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-46 MUST NOT Constraint

47. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-47 MUST COVER Constraint

48. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-48 HighLine University

49. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-49 HighLine University

50. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-50 Design for Minimum Cardinality 4 possibilities –O-O FK = null allowed Do nothing! –O-M –M-O –M-M

51. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-51 When Parent =M

52. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-52 When Child = M

53. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-53 Actions to apply

54. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-54 Minimum Cardinality

55. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-55 Minimum Cardinality

56. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-56 View Ridge

57. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-57 View Ridge

58. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-58 View Ridge

59. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-59 View Ridge

60. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 6-60 David M. Kroenke’s Database Processing Fundamentals, Design, and Implementation (10 th Edition) End of Presentation: Chapter Six Part Two