1. An Introduction to Data Modelling Entity Relationship Modelling Avin Mathew amathew@smsmt.com Nov 2010

2. WHY do we model data? 2

3. WHAT is a data model? 3

4. 4 An album has an a creating artist, a title, recommended price, genre and album art that is displayed to a user. A user can subsequently purchase the album in various quantities and at different unit prices depending on specials on offer. A user’s purchase order will contain the date of purchase, their contact details (address, telephone and/or email) and the total price.

6. WHERE do we use data models? 6

7. WHEN would a Business Analyst use data models? 7

8. Data Model Levels Conceptual Logical Physical

9. How do we data model? People Business, users, developers, DBAs Inputs Business & functional requirements, business processes, databases, documents, UI screens Tools Drawing packages (e.g. PowerPoint, Visio), data modelling packages (e.g. ERWin, System Architect)

10. Entity Relationship Model Most common data modelling technique Used in most business information system development Tools that engineer a database from a data model

11. ER Process 1.Identify entities 2.Identify attributes 3.Identify relationships 4.Apply naming conventions 5.Assign keys 6.Normalise

12. Identify entities An object that exists and is distinguishable from other objects Examples: person, company, event, place Should be a singular concept 12

13. Identify attributes Properties of an entity 13

14. One to many Identify relationships An association between two entities Cardinality and optionality One to one Many to many Roles 14

15. Apply naming conventions Examples: Singular vs plural names for entities Consistent names: date, summary, description, name Reference Types all ending with Type Standardise suffixes: Id, Key, Code, Flag 15

16. Assign keys 16

17. Normalise Every non-key attribute in every table is directly dependent on the key Results in: Elimination of redundancies Fewer anomalies Most information systems are in third-normal form 17

18. Scenario 1 18

19. Scenario 1 – A Possible Data Model 19

20. Scenario 2 20

21. Scenario 2 – A Possible Data Model 21

22. Data Model Patterns David Hay – Data model patterns: Conventions of thought Martin Fowler – Analysis patterns: Reusable object models Len Silverston – The data model resource book: A library of universal data models for all enterprises

23. An Introduction to Data Modelling Entity Relationship Modelling Avin Mathew amathew@smsmt.com Nov 2010

24. What else is there to data modelling? Association entities Identifying vs non-identifying relationships Normalisation vs de-normalisation Optionality Classes of data (reference, master, transactional) Temporal data modelling Physical modelling Treatment of inheritance 24