Presentation is loading. Please wait.

Presentation is loading. Please wait.

Database Design & Mapping

Similar presentations

Presentation on theme: "Database Design & Mapping"— Presentation transcript:

1 Database Design & Mapping
Database Application SAK 3408 Database Design & Mapping

2 Database System Design
User views of data. Conceptual data model. Implementation (relational) data model. Physical data storage. Class diagram that shows business entities, relationships, and rules. Indexes and storage methods to improve performance. List of nicely-behaved tables. Use data normalization to derive the list.

3 The Need for Design Goal: To produce an information system that adds value for the user Reduce costs Increase sales/revenue Provide competitive advantage Objective: To understand the system To improve it To communicate with users and IT staff Methodology: Build models of the system

4 Designing Systems Designs are a model of existing & proposed systems
They provide a picture or representation of reality They are a simplification Someone should be able to read your design (model) and describe the features of the actual system. You build models by talking with the users Identify processes Identify objects Determine current problems and future needs Collect user documents (views) Break complex systems into pieces and levels

5 Design Stages Initiation Physical Design Requirements Analysis
Scope Feasibility study Cost & Time estimates Requirements Analysis User Views & Needs Forms Reports Processes & Events Entity & Attributes Conceptual Design Models Data flow diagram Entity Relationships Objects User feedback Physical Design Table definitions Application development Queries Forms Reports Application integration Data storage Security Procedures Implementation Training Purchases Data conversion Installation Evaluation & Review

6 Initial Steps of Design
1. Identify the exact goals of the system. 2. Talk with the users to identify the basic forms and reports. 3. Identify the data items to be stored. 4. Design the classes (tables) and relationships. 5. Identify any business constraints. 6. Verify the design matches the business rules.

7 Business Rule BR are important in data modelling because they govern how data are – handled and stored. Basic BR : Data names Data definition Names and definition must provide for : Entity types Attribut Relationship

8 Guideline Data Names Relate to business – customer \ File10
Be meaningful – avoid is, it, has Be unique – homeadd, campusadd Repeatable–studbirthdate, stafbirthdate

9 Data Definition “ A course is a module of instruction in a particular area.” “A customer may request a model car from a rental branch in a particular date.” Guideline : A definition will state such characteristics of the data objects. Whether the data is singular or plural Who determine the value for the data Whether data is static or changes over time Whether the data is optional or an empty Where, when and how data is created.

10 The E-R Model E-R model – a logical representation of the data for an organization or for a business area E-R diagram – a graphical representation of an entity-relationship model

11 E-R Model Constructs Entity Attribute Relationship

12 Figure 2.4 Basic E-R Notation
A special entity that is also a relationship Entity symbols Attribute symbols Relationship symbols

13 Figure 2.3 Sample E-R Diagram

14 Entity An entity is a person, place, object, event or concept in the user environment about which the organization wishes to maintain data. Ex: Person – EMPLOYEE, STUDENT, PATIENT Place – STORE, WAREHOUSE, STATE Object – MACHINE, BUILDING, AUTOMOBILE Event – SALE, REGISTRATION, RENEWAL Concept – ACCOUNT, COURSE Entity type, entity instances, strong entity, weak entity

15 Entity Type vs. Entity Instance
Share common characteristic Given a name (CAPITAL LETTER) Rectangle Collection of entities (often corresponds to a table). Ex: EMPLOYEE Entity Instances a single occurrence of an entity type (often corresponds to a row in a table) Ex: may be 100 of instances of entity EMPLOYEE stored in database.

16 Entity Type vs. Entity Instance (cont.)
Entity Type : EMPLOYEE Attribut : EMP_NUM CHAR(10) NAME CHAR(25) STATE CHAR(35) 2 instances of EMPLOYEE : Ali Amir Perak Kedah

17 Strong vs. Weak Entity Types
Strong Entity Type entity that exists independently of other entity types Unique characteristic Called an identifier Ex: STUDENT, EMPLOYEE Weak Entity Type entity type whose existence depends on some other entity type No meaning in ERD without strong entity.

18 Figure 2.10 Strong and weak entities
Identifying relationship Strong entity Weak entity

19 Attribute property or characteristic of an entity type (often corresponds to a field in a table) Ex: entity type – STUDENT Attributes – name, add, id, program Simple att vs composite att. Single-valued att vs multivalued att Stored att vs derived att Identifier att.

20 Simple vs. Composite Attribute
Simple attribute – cannot broken into smaller components Composite attribute – can broken into component parts

21 Simple key attribute The key is underlined

22 a) Composite attribute
An attribute broken into component parts

23 b) Composite key attribute
The key is composed of two subparts

24 Single-Valued vs. Multivalued Attribute
Single-Valued – each of the attributes has one value Multivalued – attribute more than one value

25 Entity with a multivalued attribute (Skill)
an employee can have more than one skill

26 Stored vs. Derived Attributes
Stored attribute – data input or set Derived Attribute – attribute whose values can be calculated from related attribute values.

27 Entity with a derived attribute (Years_Employed)
from date employed and current date

28 Identifiers (Keys) Identifier (Primary Key) - An attribute (or combination of attributes) that uniquely identifies individual instances of an entity type Composite Identifier – an identifier that consists of a composite attribute. Candidate Key – an attribute that could be a key…satisfies the requirements for being a key

29 Characteristics of Identifiers
Will not change in value Will not be null No intelligent identifiers (e.g. containing locations or people that might change) Substitute new, simple keys for long, composite keys

30 Ex: identifier The key is composed of two subparts

31 Relationship Relationship
link between entities (corresponds to primary key-foreign key equivalencies in related tables)

32 Relationships (cont.) Relationship Types vs. Relationship Instances
The relationship type is modeled as the diamond and lines between entity types…the instance is between specific entity instances

33 Figure 2.6 (a) Relationship type
Figure 2.6 (b) Entity and Relationship instances

34 Relationships (cont.) Relationships can have attributes
These describe features pertaining to the association between the entities in the relationship Two entities can have more than one type of relationship between them (multiple relationships) Associative Entity = combination of relationship and entity

35 Degree of Relationships
Degree of a Relationship is the number of entity types that participate in it Unary Relationship Binary Relationship Ternary Relationship

36 Figure 2.7 Degree of relationships
Entities of two different types related to each other One entity related to another of the same entity type Entities of three different types related to each other

37 Cardinality of Relationships
One – to – One Each entity in the relationship will have exactly one related entity One – to – Many An entity on one side of the relationship can have many related entities, but an entity on the other side will have a maximum of one related entity Many – to – Many Entities on both sides of the relationship can have many related entities on the other side

38 Figure 2.8 Degree of relationships and Cardinality
(a) Unary relationships

39 (b) Binary relationships

40 (c) Ternary relationships
Note: a relationship can have attributes of its own

41 Cardinality Constraints
Cardinality Constraints - the number of instances of one entity that can or must be associated with each instance of another entity. Minimum Cardinality If zero, then optional If one or more, then mandatory Maximum Cardinality The maximum number 29

42 Figure 2.8 Cardinality Mandatory and Optional

43 Figure 2.9 Cardinality Constraints
(a) Basic relationship with only maximum cardinalities showing (b) Mandatory minimum cardinalities

44 Figure 2.10 Examples of multiple relationships
Employees and departments – entities can be related to one another in more than one way

45 Strong vs. Weak Entities, and Identifying Relationships
Strong entities exist independently of other types of entities has its own unique identifier represented with single-line rectangle Weak entity dependent on a strong entity…cannot exist on its own Does not have a unique identifier represented with double-line rectangle Identifying relationship links strong entities to weak entities represented with double line diamond

46 Associative Entities It’s an entity – it has attributes
AND it’s a relationship – it links entities together When should a relationship with attributes instead be an associative entity? All relationships for the associative entity should be many The associative entity could have meaning independent of the other entities The associative entity preferably has a unique identifier, and should also have other attributes The associative may be participating in other relationships other than the entities of the associated relationship Ternary relationships should be converted to associative entities

47 Figure 2.11 An associative entity
(a) An associative entity (CERTIFICATE) Associative entity involves a rectangle with a diamond inside. Note that the many-to-many cardinality symbols face toward the associative entity and not toward the other entities 21

48 (b)Ternary relationship as an associative entity

49 Relation Requirements:
Definition: A relation is a named, two-dimensional table of data Table is made up of rows (records), and columns (attribute or field) Not all tables qualify as relations Requirements: Every relation has a unique name. Every attribute value is atomic (not multivalued, not composite) Every row is unique (can’t have two rows with exactly the same values for all their fields) Attributes (columns) in tables have unique names The order of the columns is irrelevant The order of the rows is irrelevant

50 Correspondence with ER Model
Relations (tables) correspond with entity types and with many-to-many relationship types Rows correspond with entity instances and with many-to-many relationship instances Columns correspond with attributes

51 Key Keys are special fields that serve two main purposes:
Primary keys are unique identifiers of the relation. Examples include employee numbers, social security numbers, etc. This is how we can guarantee that all rows are unique Foreign keys are identifiers that enable a dependent relation (on the many side of a relationship) to refer to its parent relation (on the one side of the relationship) Keys can be simple (a single field) or composite (more than one field) Keys usually are used as indexes to speed up the response to user queries

52 Foreign Key (implements 1:N relationship between customer and order)
Primary Key Foreign Key (implements 1:N relationship between customer and order) Combined, these are a composite primary key (uniquely identifies the order line)…individually they are foreign keys (implement M:N relationship between order and product)

53 Transforming E-R into Relations
Step 1: Mapping Regular Entities to Relations Simple attributes: E-R attributes map directly onto the relation Composite attributes: Use only their simple, component attributes Multi-valued Attribute - Becomes a separate relation with a foreign key taken from the superior entity

54 Figure 2.12 Mapping a regular entity
(a) CUSTOMER entity type with simple attributes (b) CUSTOMER relation

55 Figure 2.13 Mapping a composite attribute
(a) CUSTOMER entity type with composite attribute (b) CUSTOMER relation with address detail

56 Figure 2.14 Mapping a multivalued attribute
Multivalued attribute becomes a separate relation with foreign key (b) 1 – to – many relationship between original entity and new relation

57 Transforming E-R into Relations
Step 2: Mapping Weak Entities Becomes a separate relation with a foreign key taken from the superior entity Primary key composed of: Partial identifier of weak entity Primary key of identifying relation (strong entity)

58 Figure 2.15 Mapping a weak entity
(a) Weak entity DEPENDENT

59 (b) Relations resulting from weak entity
NOTE: the domain constraint for the foreign key should NOT allow null value if DEPENDENT is a weak entity Foreign key Composite primary key

60 Transforming E-R into Relations
Step 3: Mapping Binary Relationships One-to-Many - Primary key on the one side becomes a foreign key on the many side Many-to-Many - Create a new relation with the primary keys of the two entities as its primary key One-to-One - Primary key on the mandatory side becomes a foreign key on the optional side

61 Figure 2.16 mapping a 1:M relationship
(a) Relationship between customers and orders

62 (b) Mapping the relationship
Foreign key

63 Figure 2.17 Mapping M:N relationship
(a) ER diagram (M:N) The Supplies relationship will need to become a separate relation

64 New intersection relation
(b) Three resulting relations Composite primary key New intersection relation Foreign key

65 Figure 2.18 Mapping a binary 1:1 relationship

66 (b) Resulting relations

67 Transforming E-R into Relations
Step 4: Mapping Associative Entities Identifier Not Assigned Default primary key for the association relation is composed of the primary keys of the two entities (as in M:N relationship) Identifier Assigned It is natural and familiar to end-users Default identifier may not be unique

68 Figure 2.19 Mapping an associative entity
(a) Associative entity

69 (b) Three resulting relations

70 Transforming E-R into Relations
Step 5: Mapping Unary Relationships One-to-Many - Recursive foreign key in the same relation Many-to-Many - Two relations: One for the entity type One for an associative relation in which the primary key has two attributes, both taken from the primary key of the entity

71 Figure 2.20 Mapping a unary 1:N relationship
(a) EMPLOYEE entity with Manages relationship (b) EMPLOYEE relation with recursive foreign key

72 Mapping a unary M:N relationship
(a) Bill-of-materials relationships (M:N) (b) ITEM and COMPONENT relations

73 Transforming E-R into Relations
Step 6: Mapping Ternary (and n-ary) Relationships One relation for each entity and one for the associative entity Associative entity has foreign keys to each entity in the relationship

74 Figure 2.21 Mapping a ternary relationship
(a) Ternary relationship with associative entity

75 Remember that the primary key MUST be unique
(b) Mapping the ternary relationship Remember that the primary key MUST be unique

Download ppt "Database Design & Mapping"

Similar presentations

Ads by Google