1. CMSC424, Spring 2005 CMSC424: Database Design Instructor: Amol Deshpande amol@cs.umd.edu

2. CMSC424, Spring 2005 Data Modeling Goals: Conceptual representation of the data “Reality” meets “bits and bytes” Must make sense, and be usable by other people Today: Entity-relationship Model Relational Model

3. CMSC424, Spring 2005 Motivation You’ve just been hired by Bank of America as their DBA for their online banking web site. You are asked to create a database that monitors: customers accounts loans branches transactions, … Now what??!!!

4. CMSC424, Spring 2005 4 Database Design Steps Three Levels of Modeling info Conceptual Data Model Logical Data Model Physical Data Model Conceptual DB design Logical DB design Physical DB design Entity-relationship Model Typically used for conceptual database design Relational Model Typically used for logical database design

5. CMSC424, Spring 2005 Entity-Relationship Model Two key concepts Entities: An object that exists and is distinguishable from other objects Examples: Bob Smith, BofA, CMSC424 Have attributes (people have names and addresses) Form entity sets with other entities of the same type that share the same properties Set of all people, set of all classes Entity sets may overlap Customers and Employees

6. CMSC424, Spring 2005 Entity-Relationship Model Two key concepts Relationships: Relate 2 or more entities E.g. Bob Smith has account at College Park Branch Form relationship sets with other relationships of the same type that share the same properties Customers have accounts at Branches Can have attributes: has account at may have an attribute start-date Can involve more than 2 entities Employee works at Branch at Job

7. CMSC424, Spring 2005 7 ER Diagram: Starting Example Rectangles: entity sets Diamonds: relationship sets Ellipses: attributes customer has cust-street cust-id cust-name cust-city account balance number access-date

8. CMSC424, Spring 2005 Rest of the class Details of the ER Model How to represent various types of constraints/semantic information etc. Design issues A detailed example

9. CMSC424, Spring 2005 Next: Relationship Cardinalities We may know: One customer can only open one account OR One customer can open multiple accounts Representing this is important Why ? Better manipulation of data Can enforce such a constraint Remember: If not represented in conceptual model, the domain knowledge may be lost

10. CMSC424, Spring 2005 Mapping Cardinalities Express the number of entities to which another entity can be associated via a relationship set Most useful in describing binary relationship sets

11. CMSC424, Spring 2005 Mapping Cardinalities One-to-One One-to-Many Many-to-One Many-to-Many customer has account customer has account customer has account customer has account

12. CMSC424, Spring 2005 Mapping Cardinalities Express the number of entities to which another entity can be associated via a relationship set Most useful in describing binary relationship sets N-ary relationships ?

13. CMSC424, Spring 2005 Next: Types of Attributes Simple vs Composite Single value per attribute ? Single-valued vs Multi-valued E.g. Phone numbers are multi-valued Derived If date-of-birth is present, age can be derived Can help in avoiding redundancy, enforcing constraints etc…

14. CMSC424, Spring 2005 Types of Attributes customer has cust-street cust-id cust-name cust-city account balance number access-date

15. CMSC424, Spring 2005 Types of Attributes customer cust-street cust-id cust-name cust-city has account balance number access-date phone no. date-of-birth age multi-valued (double ellipse) derived (dashed ellipse)

16. CMSC424, Spring 2005 Types of Attributes customer cust-street cust-id cust-name cust-city has account balance number access-date phone no. date-of-birth age month dayyear Composite Attribute

17. CMSC424, Spring 2005 Next: Keys Key = set of attributes identifying individual entities or relationships

18. CMSC424, Spring 2005 customer cust-street cust-id cust-name cust-city phone no. age date-of-birth Possible Keys: {cust-id} {cust-name, cust-city, cust-street} {cust-id, age} cust-name ?? Probably not. Domain knowledge dependent !! Entity Keys

19. CMSC424, Spring 2005 Entity Keys Superkey any attribute set that can distinguish entities Candidate key a minimal superkey Can’t remove any attribute and preserve key-ness {cust-id, age} not a superkey {cust-name, cust-city, cust-street} is assuming cust-name is not unique Primary key Candidate key chosen as the key by DBA Underlined in the ER Diagram

20. CMSC424, Spring 2005 Entity Keys {cust-id} is a natural primary key Typically, SSN forms a good primary key Try to use a candidate key that rarely changes e.g. something involving address not a great idea customer cust-street cust-id cust-name cust-city phone no. age date-of-birth

21. CMSC424, Spring 2005 Relationship Set Keys What attributes are needed to represent a relationship completely and uniquely ? Union of primary keys of the entities involved, and relationship attributes {cust-id, access-date, account number} describes a relationship completely customer has cust-id account number access-date

22. CMSC424, Spring 2005 Relationship Set Keys Is {cust-id, access-date, account number} a candidate key ? No. Attribute access-date can be removed from this set without losing key-ness In fact, union of primary keys of associated entities is always a superkey customer has cust-id account number access-date

23. CMSC424, Spring 2005 Relationship Set Keys Is {cust-id, account-number} a candidate key ? Depends customer has cust-id account number access-date

24. CMSC424, Spring 2005 Relationship Set Keys Is {cust-id, account-number} a candidate key ? Depends customer has cust-id account number access-date If one-to-one relationship, either {cust-id} or {account-number} sufficient Since a given customer can only have one account, she can only participate in one relationship Ditto account

25. CMSC424, Spring 2005 Relationship Set Keys Is {cust-id, account-number} a candidate key ? Depends customer has cust-id account number access-date If one-to-many relationship (as shown), {account-number} is a candidate key A given customer can have many accounts, but at most one account holder per account allowed

26. CMSC424, Spring 2005 Relationship Set Keys General rule for binary relationships one-to-one: primary key of either entity set one-to-many: primary key of the entity set on the many side many-to-many: union of primary keys of the associate entity sets n-ary relationships More complicated rules

27. CMSC424, Spring 2005 Next: Data Constraints Representing semantic data constraints We already saw constraints on relationship cardinalities

28. CMSC424, Spring 2005 Participation Constraint Given an entity set E, and a relationship R it participates in: If every entity in E participates in at least one relationship in R, it is total participation partial otherwise

29. CMSC424, Spring 2005 29 Participation Constraint customer has cust-street cust-id cust-name cust-city account balance number access-date Total participation

30. CMSC424, Spring 2005 Cardinality Constraints customer has cust-id account number access-date 0..*1..1 How many relationships can an entity participate in ? Minimum - 0 Maximum – no limit Minimum - 1 Maximum - 1

31. CMSC424, Spring 2005 Next: Recursive Relationships Sometimes a relationship associates an entity set to itself

32. CMSC424, Spring 2005 Recursive Relationships Must be declared with roles employee works-for emp-street emp-id emp-name emp-city manager worker

33. CMSC424, Spring 2005 Next: Weak Entity Sets An entity set without enough attributes to have a primary key E.g. Transaction Entity Attributes: transaction-number, transaction-date, transaction-amount, transaction-type transaction-number: may not be unique across accounts

34. CMSC424, Spring 2005 Weak Entity Sets A weak entity set must be associated with an identifying or owner entity set Account is the owner entity set for Transaction

35. CMSC424, Spring 2005 Weak Entity Sets account balance number Transaction has trans-type trans-number trans-date trans-amt Still need to be able to distinguish between different weak entities associated with the same strong entity

36. CMSC424, Spring 2005 Weak Entity Sets account balance number Transaction has trans-type trans-number trans-date trans-amt Discriminator: A set of attributes that can be used for that

37. CMSC424, Spring 2005 Weak Entity Sets Primary key: Primary key of the associated strong entity + discriminator attribute set For Transaction: {account-number, transaction-number}

38. CMSC424, Spring 2005 Next: Specialization Consider entity person: Attributes: name, street, city Further classification: customer Additional attributes: customer-id, credit-rating employee Additional attributes: employee-id, salary Note similarities to object-oriented programming

39. CMSC424, Spring 2005 Specialization: Example

40. CMSC424, Spring 2005 Finally: Aggregation No relationships between relationships E.g.: Associate account officers with has account relationship set customer has account account officer employee ?

41. CMSC424, Spring 2005 Finally: Aggregation Associate an account officer with each account ? What if different customers for the same account can have different account officers ? customer has account account officer employee ?

42. CMSC424, Spring 2005 Finally: Aggregation Solution: Aggregation customer has account account officer employee

43. CMSC424, Spring 2005 More… Read Chapter 2 for: Specialization/Aggregation details Different types of specialization’s etc Generalization: opposite of specialization Lower- and higher-level entities Attribute inheritance …

44. CMSC424, Spring 2005 An Example: Employees can have multiple phones E/R Data Model Design Issue #1: Entity Sets vs. Attributes Employee Phone Uses vs (a) (b) To resolve, determine how phones are used 1. Can many employees share a phone? (If yes, then (b)) 2. Can employees have multiple phones? (if yes, then (b), or (a) with multivalued attributes) 3. Else (a), perhaps with composite attributes Employee phone_no phone_loc no loc no loc phone

45. CMSC424, Spring 2005 An Example: How to model bank loans E/R Data Model Design Issue #2: Entity Sets vs. Relationship Sets vs (a) To resolve, determine how loans are issued 1. Can there be more than one customer per loan? If yes, then (a). Otherwise, loan info must be replicated for each customer (wasteful, potential update anomalies) 2. Is loan a noun or a verb? Both, but more of a noun to a bank. (hence (a) probably more appropriate) Customer (b) Loans Branch Customer Loan Borrows lno amt ssn name ssn name lno amt bname bcity

46. CMSC424, Spring 2005 An Example: Works_At E/R Data Model Design Issue #3: N-ary vs Binary Relationship Sets Employee Works_at Branch Dept Employee WA E Branch Dept WA Binary: Ternary: WA B WA D vs (Joe, Moody, Acct)  Works_At (Joe, w 3 )  WA E (Moody, w 3 )  WA B (Acct, w 3 )  WA D Choose n-ary when possible! (Avoids redundancy, update anomalies)

47. CMSC424, Spring 2005 Example Design We will model a university database Main entities: Professor Projects Departments Graduate students etc…

48. CMSC424, Spring 2005 professor area name SSN rank project start sponsor proj-number budget dept office name dept-no homepage grad age name SSN degree

49. CMSC424, Spring 2005 professor area name SSN rank project start sponsor proj-number budget dept office name dept-no homepage grad age name SSN degree

50. CMSC424, Spring 2005 professor area name SSN rank project start sponsor proj-number budget dept office name dept-no homepage grad age name SSN degree PI Co-PI RA Major Chair Supervises Mentor advisee advisor Appt Time (%)

51. CMSC424, Spring 2005 professor area name SSN rank project start sponsor proj-number budget dept office name dept-no homepage grad age name SSN degree PI Co-PI RA Major Chair Appt Supervises Mentor advisee advisor Time (%)

52. CMSC424, Spring 2005 professor area name SSN rank project start sponsor proj-number budget dept office name dept-no homepage grad age name SSN degree PI Co-PI RA Major Chair Appt Supervises Mentor advisee advisor Time (%) And so on…

53. CMSC424, Spring 2005 Summary Entity-relationship Model Intuitive diagram-based representation of domain knowledge, data properties etc… Two key concepts: Entities Relationships We also looked at: Relationship cardinalities Keys Participation Constraints …

54. CMSC424, Spring 2005 Summary Details unimportant Key idea: We can represent many data properties and constraints conceptually using this Read Chapter 2 Assignment will require you to do this anyway !