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Home > Training > Data Warehousing > Advanced Data Modeling Training

Advanced Data Modeling Training

Course#: WA1823

This is a workshop and relies on realistic exercises. You will learn how to apply leading edge data modeling principles to practical and difficult modeling situations. All of the exercises have been derived from real modeling situations.

What you will learn

This workshop addresses all of the issues that trouble the experienced practicing data modeler:

  • how far to abstract in the data model
  • how to deal with time and history
  • how to deal with complex business rules, how to represent entity life histories
  • how to interrelate data and process models
  • how to reconcile data modeling concepts with object oriented concepts.

Data analysts, data administrator, data base designers, system analysts and designers, and other practicing data modelers.

4 day

Outline of WA1823 Advanced Data Modeling 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

14. Summary and Conclusion

We regularly offer classes in these and other cities. Atlanta, Austin, Baltimore, Calgary, Chicago, Cleveland, Dallas, Denver, Detroit, Houston, Jacksonville, Miami, Montreal, New York City, Orlando, Ottawa, Philadelphia, Phoenix, Pittsburgh, Seattle, Toronto, Vancouver, Washington DC.
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