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Advanced Data Modeling

 

Course Description | Course Outline | Data Warehousing | IT Training

1. Review of Data Modeling

  • Entity
  • Attribute
  • Relationship
  • Constraint
  • Domain
  • Derived Data

2. Business Rules

  • Types of business rules
  • Static (association) rules
  • Dynamic (processing) rules
  • Sources of business rules
  • Methods of recording business rules
  • Assigning business rules with most reusable element

3. Creating Data Views

  • List of the data used
  • Attribute characteristics:
  • Create, read, update, delete
  • Mandatory, optional, prohibited, postponed
  • Assignment of rules to the data
  • Static rule assignment
  • Dynamic rule assignment

4. Modeling Time and Change

  • Short term and long term view
  • Five methods for dealing with time
  • Derived data
  • Capturing business changes
  • Importance of representing the business time dimension

5. Abstractions in Data Modeling

  • Abstraction in general
  • Aggregation
  • Generalization
  • Subtyping
  • Rules
  • Inheritance
  • Single Inheritance
  • Multiple Inheritance
  • Other Characteristics
  • "Member Of" Relationship

6. Inheritance Rules

  • One-to-many relationship
  • Inheritance in "member of" relationships
  • Distinction of "member of" from subtyping
  • Practical examples
  • Other characteristics

7. Flexibility in Models

  • Different meanings of flexibility
  • Limitations of subtyping
  • Abstracting to generalize
  • Using type coding
  • Creating extensible models
  • Generalizing business rules

8. Different Kinds of Relationships

  • Complex relationships
  • Relationship constraints
  • Mutually exclusive and inclusive relationships

9. Entity Life Histories

  • Rules for
  • Value of
  • Syntax rules
  • Examples

10. Process Discovery Methods

  • Event analysis:
  • External events
  • Temporal events
  • Data triggers
  • Object analysis
  • Entity life histories
  • CRUD matrices and others

11. Model Reconciliation

  • Importance of parallel model development
  • Various methods available
  • CRUD Matrix
  • Data views
  • Usage maps
  • Other Methods

12. Object Orientation Review

  • Characteristics of an object
  • Classification
  • Encapsulation
  • Inheritance
  • Message passing (and polymorphism)
  • Definition of an object
  • Relationship Of OO to data modeling
  • Use of existing modeling methods in OO

13. Data Design Compromises

  • Safe compromises for optimization
  • Aggressive compromises for optimization
  • Integrity/redundancy compromises