Bite sized training sessions: Data Modelling – Part 1 of 2 Data Model Diagrams

1. Bite sized training sessions:Data Modelling – Part 1 of 2Data Model Diagrams Feb 2011 Prepared by Guy Beauchamp Group Projects & IT

2. Objectives To understand What is a data model … and what it is not! Why do data modelling To be able to Read a data model Build a data model Critically review a data model

3. What is a data model? Specification of the data that is required in order for The solution to meet it’s objectives Processes to be able to run A data model comprises: A diagram showing the requireddata dependencies A set of data definitions required foreach attribute on the diagram Also referred to as: Logical Data Model (LDM) Entity Model Entity Relationship Diagram (ERD) Data Dictionary Object Model Class Diagram Data Structure …etc!

4. What a data model is not A physical design for storing data A database design Database table definitions Object specification

5. Why do data modelling? Data & Process Requirements Designed As Designed As Designed As Designed As Physical data Specs Manual Procedures Manipulate Database Designs System Specs Manipulate Solution Specification

6. Data Model Components Entity A real world thing or an interaction between 2 or more real world things. Relationship How and why entities depend on each other (the relationship) and what that relationship is (the cardinality of the relationship). Attribute The atomic pieces of information that we need to know about entities.

7. Entity “A real world thing or an interaction between 2 or more real world things.” • A real world thing • E.g. Customer, Product • An event between 2 or more entities • E.g. Sale

8. ‘Type’ Entities • Categorises other entities • Holds information that applies to sets of other entities • Very common • Typical relationship cardinality is mandatory 1:M • Relationship names add little value

9. Relationships “How entities depend on each other in terms of why the entities depend on each other (the relationship) and what that relationship is (the cardinality of the relationship).” There are dependency business rules between two entities – can be shown as: NB: there are other notations.

10. Relationship Names Always name relationships in at least one direction (except for those involving Type entities) Especially useful when there is more than one relationship between two entities:

11. Reading relationships One Customer (entity)may (cardinality) purchase (relationship name)one or more (cardinality) SALEs (entity) One SALE must be purchased by one CUSTOMER Tip – start with the word “One”, never “MANY”

12. Attributes “The atomic pieces of information that we need to know about entities” Customer(entity) Sale Product

13. Primary Keys • A special kind of attribute, set of attributes and/or relationships • Is the way for the business to identify 1 unique instance of an entity • Certain rules apply to a primary key: • Must not be repeated within an entity • Once assigned can never be updated (only deleted) • Must be the way that the business uniquely identify an instance of an entity Customer(entity) Which attribute makes the best primary key? Why?

14. Primary Keys are the navigation method for relationships Customer(entity) Purchased Sale Discussion: What is the PK of Sale? Do PKs need to be shown at the ‘FK’ end of a relationship? Purchased via Product

15. 5 Data Modelling “No-No”s • No repeating attributes on entities • E.g. On a Customer entity “1st child name”, “2nd child name”… • No attributes on entities that do not depend on the primary key • E.g. On Customer entity “order date” • No “Many to Many”s between entities • E.g. Product ordered by many customers, a customer orders many products • No “one to one”s between entities (usually) • E.g. Customer has one Membership Card and a Membership Card is for one Customer • No circular relationships between entities (usually) • E.g. next slide

16. Circular relationships

17. Circular relationships How do we fix this circular relationship?

18. Process for producing a data model diagram • identify candidate entities • select a central candidate entity • define the primary key • work through the rest of the candidate entities • consider whether it is in scope • define the primary key • define the relationship(s) between the candidate entity and all other candidate entities on the diagram • create description entities as needed • fully express the cardinality of the relationship(s) • name the relationship(s) as needed • validate everything with the user • review and refine.

19. Next step: Data definitions……covered in part 2 of this bite sized training session

20. Minor Exercise I own a florist’s shop called My Florist. I want to start emailing reminders to customers when special occasions are due for which they have brought flowers in the past – for example a spouse’s birthday. Let’s draw up a data model to support that process.

21. An answer…

22. Major Exercise • You are business analysts working for a company called re-Evolution Coffee Houses Ltd • You have been given a piece of work – ref handouts • Produce a data model showing • Entities • Primary Keys • Relationships • Suggestion: follow the process for producing a data model diagram 4 slides previously • The business users will be available for questions

23. Major Exercise • If you need to make an assumption about business requirements or anything else then document it • Time allowed: 1 hour • Deliverable: • Flip chart data model • Flip chart assumptions • Be prepared to present your data model to the other team • Don’t worry about completing the exercise • Do worry about the quality of what you get through

24. …and finally • Any questions? • Further resources… • Feedback • Thank-you!