Presentation is loading. Please wait.

Presentation is loading. Please wait.

Monica Farrow EM G30 Material on Vision Er 1 F28DM: Database Management Systems The Entity Relationship Model.

Similar presentations


Presentation on theme: "Monica Farrow EM G30 Material on Vision Er 1 F28DM: Database Management Systems The Entity Relationship Model."— Presentation transcript:

1 Monica Farrow EM G30 Material on Vision Er 1 F28DM: Database Management Systems The Entity Relationship Model

2 Er 2 Topics today Conceptual database design ER diagrams Notation Definitions Entities Relationships Cardinality constraints Participation constraints Limitations (other constraints) Fan and chasm traps Extended ER diagram Examples – Departmental, Hospital

3 Er 3 Database Design Database design goes through several stages. Physical Database Design Logical Database Design Data Analysis, Conceptual Design Problem Data Requirements Conceptual Data Model Storage structure and File Organisation Logical Schema Requirements Analysis

4 Er 4 Conceptual Database Design Process of constructing a model of the data used in an enterprise, independent of all physical considerations. E.g. ER diagram Conceptual database design is top-down design as you start by specifying entities (real-world objects) then build up the model by defining new entities, attributes, and relationships. The data model is built using the information in the users’ requirements specification. The conceptual data model is the source of information for logical design phase. © Pearson Education Limited 1995, 2005

5 Er 5 Conceptual Design with the ER Model The questions we need to ask are: 1. What are the entities (e.g. objects, individuals) in the organisation? 2. Which relationships exist among these entities? 3. What information do we want to store about these entities and relationships? 4. What are the business rules of the organisation? 5. Which integrity constraints do arise from them? The answers are mostly represented in an Entity Relationship diagram

6 Er 6 ER Diagrams There are quite a few different notations for ER diagrams In year one, we used UML notation Chen and Crow’s Foot notations are also commonly used There are others as well..... We’ll look at these 2 notations and some variations as we look at the components of an ER diagram

7 Er 7 No RDBMS design decisions! At this stage, we are ONLY concerned with modelling entities in the real world, and the connections between them, as we need it for our database requirements We are NOT thinking about how to store the data in the tables So you will see some representations of data that will have to be changed when converting into tables Don’t include foreign keys at this stage We COULD use the ER diagram as a basis for an Object Oriented database

8 Er 8 UML notation In this diagram 2 Entities (SpyMaster, Spy) are connected by a relationship One SpyMaster manages at least one and maybe multiple Spies One Spy is managed by exactly one master. A Spy has attributes (name, date of birth etc) The codeName uniquely identifies the Spy, and is used as a primary key. Spy codeName {PK} firstName dateOfBirth gender mark amountDue SpyMaster mCodeName {PK} contact 1.. * 1 manage s

9 Er 9 Other notations This shows the same information as the previous slide, using Chen notation Crow’s feet notation is similar to UML notation, with different symbols on the relationships 1 Spy SpyMaster mCode Name contact code Name firstName etc manages n

10 Er 10 Example ER Diagram for a Company database A company has several departments. Each department has a unique number and a unique name, and may be based in several locations (e.g. Hillhead, Overton, MillEnd). A department has a manager. A department controls various projects. Projects also have a unique ID and name, and several deadlines (e.g. startup, intermediate, final). Information required about the employee is a unique ssn (social security number), his name, date of birth, age, gender, salary. We don’t need to know about which employee works at which location. An employee works for one department and may work on several projects. The number of hours that they are allocated for each project must be recorded. Most employees are supervised by another employee.

11 Er 11 Company ER Diagram Assumes we only want to know about which depts in which locations, not which employee in which location etc Department dept number {PK} dept name {AK} location [1..5] Employee ssn {PK} name first names last names date of birth gender salary /age 1..* 1 works for manages Project proj number {PK} project name {AK} 1..* 0..* controls hours works on 1 1..* has 1 0..* supervises 0..* 0..1 Deadlines date type start date

12 Er 12 Entity Entity: a thing or object of importance, about which data must be captured A entity is described by a set of attributes and may have relationships with other entities Entities can be objects with a physical existence E.g. Employee, Department Or with a conceptual or abstract existence E.g. deadline

13 Er 13 Entity Type, Entity occurrence Entity Type (or Set): A group of objects with the same properties E.g. all employees in the system Entity Occurrence: A uniquely identifiable object of an entity type E.g a particular employee “John Smith” An entity set consists of entity occurrences and can be shown in a semantic net like this: John Smith Tim Grey Amy White

14 Er 14 Attributes 1 An attribute is a property of an entity or a relationship type E.g Employee name, staff number, date of birth The attribute domain is the set of allowable values E.g.: 6 digits for the staff number Up to 20 characters for a name A set of building names (Earl Mountbatten, David Brewster etc)

15 Er 15 Simple or composite Attributes can be simple or composite Staff number is just 6 digits – simple Name could be divided into first names and last name. Date of birth consists of day, month, year Decide whether to model name as a simple attribute or to subdivide it, depending on how it will be used in the application As individual components, or not Show composite attributes indented Employee ssn {PK} name first names last name date of birth gender

16 Er 16 Single and multi-valued attributes Single and multi-valued Most attributes are single-valued (date of birth, name) A company may have 3 telephone numbers – multi- valued A department may have different locations Show permitted number of attributes in square brackets Room roomID {PK} tel [1..3]

17 Er 17 Derived attribute A derived attribute is an important attribute, but one that should be calculated from other data E.g. we often need to know a person’s age, but this changes over time. It is best just to work it out when we need it. Precede with a slash Likely usage - fairly rare Eg. result of calculation such as duration, age, actual miles per gallon of car Employee ssn {PK} name first names last name date of birth /age

18 Er 18 Keys A minimal set of attributes which uniquely identifies each occurrence of an entity type is called a candidate key E.g. Employee could be identified by staff number or NHS number Names are a poor choice of key, they might not be unique Select one candidate key to uniquely identify the entity in your system – the primary key E.g. staff number. Often there is only one candidate key Show primary keys with {PK} Alternative or candidate keys {AK} Employee ssn {PK} nhsNo {AK} name first names last name date of birth gender

19 Er 19 Problems with keys Sometimes it might be hard to choose a key An Address entity Street number and postcode? Do all addresses fit this pattern? A Volunteer for a charity May not be assigned any sort of id number Name might not be unique Invent one? E.g. initials and sequence number Use an ‘autonumber’ – meaningless but unique This problem should be noted but decisions can be delayed until later in the design.

20 Er 20 Composite key A candidate key that consists of more than one attribute is called a composite key i.e. more than one attribute is needed to make the entity unique E.g. Keep a list of company contacts. Some companies have branches in various towns. So the company name and the town is needed to identify the company. CompanyContact company name {PK} town {PK} contact name contact phone

21 Er 21 Strong and weak entity types A strong entity is not existence-dependent upon other entities Employee and Department entities both exist in a company A weak entity is existence-dependent upon some other entity. Details about this weak entity would not be kept in the database without the other entity, and it cannot be uniquely identified without knowing about the associated entity. E.g. the details of one item in an order

22 Er 22 Strong and weak entity types Weak entities are quite confusing, and there can quite often be a debate as to whether an entity is weak or not It’s not possible to identify candidate keys for a weak entity Think about possible OrderItem entities Order 5 could contain an order for 10 of item number 51 Order 6 could also contain an entry for 10 of item number 51 We need to include the order number to make the entry unique – but don’t do this in the ER diagram, leave as a weak entity Order order number {PK} customer number date of order OrderItem Item number quantity 1 has 1..*

23 Er 23 Strong and weak entity types At this stage, another way of thinking about the weak entity is to consider it as a composite multivalued attribute: Order order number {PK} customer number date of order order item [1..*] item number quantity

24 Er 24 Relationships Relationship: An association among 2 or more entities. (example on next slide) In UML notation, the relationship should be labelled, and a black triangle indicates the direction that the label should be read E.g. Employee works on Project Relationships may have attributes E.g. Employee John Smith works on Project X for 10 hours We can also show how many entities participate in the relationships, shown here using 1..* More about this in a later slide

25 Er 25 Relationships example Project proj number {PK} project name Employee ssn {PK} name first names last names date of birth 1..* works on hours

26 Er 26 Relationships Relationship Type or Set: A collection of similar relationships The Set is the set of all lines in the semantic net below Relationship occurrence: a uniquely identifiable association, which includes one occurrence from each particpating entity type E.g. John Smith works on project X Each line below is an occurrence John Smith Tim Grey Amy White X A RR X

27 Er 27 Relationships There may be more than one relationship between 2 entity types Department dept number {PK} Dept name Employee ssn {PK} name first names last names date of birth 1..* 1 works for 1 1 manages

28 Er 28 Complex relationships Introduce a diamond (as in Chen notation) to represent relationships between more than two entity types For a particular course and programme, there can be many students. It’s possible that no students choose this course for a programme. For a particular student and course, they are only taking one programme For a particular student and programme, there should be 8 courses – but allow less in case of exemptions Programme Student Course studies 0..*

29 Er 29 Exceptions to the rule Never impose ‘normal’ constraints on a database system if there could be exceptions to the rule! E.g. The normal number of courses for a student to take is 8, but occasionally students may take more or less. More if repeating a course from previous year Less if some sort of part-time arrangement

30 Er 30 Recursive relationships A recursive relationship is when an entity has a relationship with itself E.g. A member of staff may supervise one or more other members of staff A member of staff may be supervised by another member of staff supervises Staff 0..* 0..1

31 Er 31 Cardinality Constraints (1) Cardinality = how many When reading, ignore the number nearest to the first entity mentioned Start sentence with ‘A’ or ‘An’ End sentence with the details in the numbers nearest the second entity A department is worked for by many employees An employee works for one department Department dept number {PK} dept name Employee ssn {PK} name first names last names date of birth 1..* 1 works for 1 1 manages

32 Er 32 Cardinality Constraints (2) Cardinality = how many 1:1 An employee manages one department A department is managed by one employee 1:Many An employee works for one department A department has many employees Department dept number {PK} dept name Employee ssn {PK} name first names last names date of birth 1..* 1 works for 1 1 manages

33 Er 33 Cardinality Constraints (2) Many : Many An employee works on many projects A project has many employees working on it Project proj number {PK} project name Employee ssn {PK} name first names last names date of birth 1..* works on hours

34 Er 34 Cardinality Constraints (3) One-to-OneOne-to-ManyMany-to-OneMany-to-Many Cardinality constraints can be shown by a semantic net

35 Er 35 Participation Constraints The participation constraint determines whether all or only some entity occurrences participate in a relationship Every department must have a manager Not all employees are managers In UML notation, the multiplicity determines optional or mandatory participation 0..* means optional 1..* means mandatory In other notations, participation may be shown by vertical bar on the relationship near the entity, or by open and closed circles, or thicker relationship lines

36 Er 36 Other constraints There are various constraints that can’t be shown on an ER diagram, for example: Domain constraints E.g. gender can only be M or F Multi-table constraints other than the relationships E.g. Employees aged under 21 cannot work on Project X E.g. The time ranges allocated to a module cannot overlap

37 Er 37 Conceptual Design using the ER Model Design Choices: Should a concept be modelled as an entity or an attribute? Should a concept be modelled as an entity or a relationship? Identifying relationships: binary or ternary Constraints in the ER Model: A lot of data semantics can (and should) be captured. Keep the initial ER model like the real world E.g. don’t show foreign keys When converting to tables, various relational database rules may change some attributes to entities

38 Er 38 Fan traps These obscure the relationship between two entities In the following, each student is attached to exactly one department as is each course, but you cannot tell which courses each student attends. Fan traps occur when two supposedly related entity types are connected only through many- to-one relationships with some third entity type Course StudentDepartment 111..*

39 Er 39 Fan traps The solution is to change which entity type is at the centre or maybe to add a new relationship Depending on whether there is a significant link between student and department, or whether the link is just through the course Student DepartmentCourse * Student Department Course * 1

40 Er 40 Chasm traps These imply relationships between entity types which do not hold In the following, it has been decided to model the student information using the intuition that a student’s department can be inferred through a supervisor. Student DepartmentSupervisor *

41 Er 41 Chasm traps However, not all students have supervisors (partial participation), so what is the department of such students? The solution is to put in a direct relationship between student and department Student Department Supervisor * 1

42 Er 42 Limitations to ER diagrams We’ve covered the basic ER diagrams An extended version (brief details on next slide) uses generalisation and specialisation to cover more complex situations In your coursework, if you find some of your constraints cannot be captured in your ER diagram, make notes of these and hand in as text.

43 Er 43 Extended ER Diagrams See diagram on the next slide Uses generalisation and specialisation ALL Employees have the attributes in the generalised superclass Employee Extra attributes must be kept according to the role of the employee (e.g. manager or sales personnel) and according to their employment category (salaried or hourly paid)

44 Er 44 Extended ER Diagrams Employee ssn {PK} name first names last names date of birth Manager mgrStartDate Salaried salary scale HourlyPaid rate SalesPersonnel salesArea (Optional, And) (Mandatory, Or)

45 Er 45 Company ER Diagram Department dept number {PK} dept name {AK} location [1..5] Employee ssn {PK} name first names last names date of birth /age 1..* 1 works for manages supervises 0..* 0..1 Manager mgrStartDate SalesPersonnel salesArea (Optional, And) Sales saleDate salePrice 1..* 1 Fragment of ER diagram showing that relationships can be shown from both the generalised and the specialised entities – as appropriate

46 Er 46 Extended ER Diagrams Participation constraints are shown with the labels (Mandatory or Optional) Employees do not have to be managers or sales personnel Employees must be salaried or hourly paid Disjoint constraints are shown with the labels (And or Or) Employees could be both a Manager AND SalesPersonnel Employees must be either Salaried OR HourlyPaid, not both

47 Er 47 Conceptual Design: Summary Conceptual design Follows requirements analysis Is performed at a high level of abstraction* involving entities, relationships and attributes Yields a high-level description of data to be stored The Entity Relationship Model is popular for conceptual design But can be very subjective * Abstraction = hiding implementation details

48 Er 48 Conceptual Design: Summary Include integrity constraints in the ER model, key constraints, participation constraints, overlap/disjoint, etc *** Foreign key constraints are implicit *** i.e. shown by the relationship lines ONLY, not described as attributes In an ER diagram, each attribute occurs only once, in the most logical place Constraints are important to determine the best DB design for an organisation


Download ppt "Monica Farrow EM G30 Material on Vision Er 1 F28DM: Database Management Systems The Entity Relationship Model."

Similar presentations


Ads by Google