1. IMS 5024 Data Modelling (1)

2. IMS 5024 Lecture 32 Content Individual assignment date Pitfall revisited Group assignment Class assignment Nature of data modelling Tools/Techniques used in data modelling Place in ISD Evaluation of data modelling Reading list

3. Date for the individual assignment Two dates appear in the hand out: –23 August 2001 –27 August 2001 (it also wrongly states that it is a Friday) What will it be!!! –27 August 2001 at 17h00!!

4. Class assignment What is this about? What conventions/rules are used? What does it depict? Where would this fit into ISD?

5. Data modelling describe: Structure Meaning Relationship Of Data

6. Data modelling help us to grasp: Static Data in the organisation Fundamental building block of the system Two perspectives (Process and Data)

7. Techniques used in Data modelling Entity relationship diagrams Normalisation Data Dictionary What difference? Use both?

8. Entity Entity – things of interest to the business Identification of an entity is subjective Entities can be: Realeg product Abstracteg Quota Event rememberedeg sale Role playedeg employee Employee

9. Relationship Relationship Between entities Cardinality (eg. One to many, one to one ect.) Degree of relationship (Unary, Binary, Ternary) DepartmentEmployee

10. Examples of Cardinalities PATIENT HISTORY PATIENT PROJECT EMPLOYEE PERSON Mandatory cardinalities Optional and mandatory cardinalities Optional cardinalities Has Is assigne d to Is married to

11. Relationship Cardinality Summary Mandatory 1 cardinality Many cardinality (1,2 …m) Optional (0 or 1) cardinality Optional (0 or many) cardinality

12. Unary Relationship Also called a recursive relationship PERSONEMPLOYEE One to manyOne to one Is married to Manages

13. Binary Relationship A binary relationship is a relationship between instances of two entity types. PROJECT EMPLOYEE SALES ORDER CUSTOMER ITEM SUPPLIER One to oneOne to manyMany to many Leads Places Supplie s

14. Ternary Relationship A ternary relationship is a relationship between instances of three entity types. PART supplies VENDORCUSTOMER

15. Attributes What we want to know about the entity or a relationship Types: – Derived, – multi-valued, –Composite, –Simple

16. Example of attributes EMPLOYEE Emp-no NameAddress Skill

17. Supertypes and subtypes Benefits: –Presentation –Creativity –Communication –Classifying common patterns –Divide and conquer Generalisation vs Specialisation

18. Example of super- and subtypes EMPLOYEE Emp-no NameAddress Skill HOURLY EMPLOYEE SALARIED EMPLOYEE CONSULTANT Contract number Stock optionHourly rate Annual salary Billing rate

19. Thinking in Data modelling Hard Vs Soft ?? Perspective –Objective vs Subjective –Nature of the organisation

20. Evaluation of Data modelling Problem orientedProduct oriented Concep- tual Structured analysis Entity relationship modelling Logical construction of systems Modern structured analysis Object oriented analysis Structured design Object oriented design Formal PSL/PSA JSD VDM Levels of abstraction Stepwise refinement Proof of correctness Data abstraction JSP Object oriented programming

21. Advantages of Data modelling Data model is not computer oriented (agree??) Model understandable by technologist and users Does not show bias UoD can vary (whole organisation or department) Readily transformable into other models Different data analysis techniques Data modelling is rule-based

22. Disadvantages Does not encourage/support user participation Your view on the organisation –people or data The idea that the model is THE model Subjective view One-side ito data Others??

23. Process modelling view of ISD Development group Objectives Environment Object system Object system Change process Hirschheim et al see reading list

24. Reading for next week Simsion, G. (1994). Data modeling essentials: Analysis, Design, and Innovation. Van Nostrand Reinhold, USA. Chapter 2, 7 and 10.