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Oracle User Conference Is Data Modeling Dead?

Oracle User Conference Is Data Modeling Dead?. DeVRY University March 20, 2006 Professor Tanya Cannon. Presentation Agenda. Introduction to System Development Life Cycle (SDLC) Process Modeling vs. Data Modeling Data Oriented Approach

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Oracle User Conference Is Data Modeling Dead?

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  1. Oracle User ConferenceIs Data Modeling Dead? DeVRY University March 20, 2006 Professor Tanya Cannon

  2. Presentation Agenda • Introduction to System Development Life Cycle (SDLC) • Process Modeling vs. Data Modeling • Data Oriented Approach • Automobile Insurance Application (AIA) - Context Data Flow Diagram • Purpose of Data Modeling • Normalization Steps • Normalization Student Example (Physical ERD) • AIA Data Model Example • Logical ERD Example • Physical ERD Example • Is Data Modeling Dead? • Open Discussion!

  3. SDLC Overview SDLC – Work Breakdown Structure (WBS)

  4. Why Follow a SDLC? The cost of finding errors increase exponentially as you go through the life cycle.

  5. Traditional vs. Modern Approach Model Driven Approaches (SA&D, IE, OOAD, etc…)

  6. Process Model vs. Data Model John Zachman Information System Framework (Knowledge is the data oriented approach) http://members.ozemail.com.au/~ieinfo/zachman.htm#WhatisFramework

  7. Context Data Flow Diagram(System Boundary)

  8. Purpose of Data Modeling Brief Data Modeling Background: • Developed by Boyce Codd (IBM) in 1970 • Considered ingenious but impractical in 1970 • Conceptually simple • Computers lacked power to implement the relational model • Today, microcomputers can run sophisticated relational database software

  9. Purpose of Data Modeling • To document the business information requirements • To identify reuse requirements and opportunities • To document data requirements based functional activity and/or business rules • To assist in identification of redundant processes • To guide and support consistent data administration

  10. Normalization • Process for evaluating and correcting table structures to minimize data redundancies. • It helps eliminate data anomalies. The three steps of data normalization.

  11. Normalization “All non-key attributes must depend on the entire primary key, and nothing but the primary key, so help me CODD.” The three steps of data normalization are: • 1NF - All repeating groups are removed • 2NF - All Partial dependencies are removed • 3NF - All Transitive dependencies are removed

  12. Normalization – Un-normalized Data

  13. Normalization – 1NF

  14. Normalization – 2NF

  15. Normalization – 3NF

  16. Normalization Results Summary

  17. Normalization - Physical ERD

  18. AIA – Data Model Example • AIA – Logical ERD Example • Normalization Occurred (Moving from Logical to Physical Model) • AIA – Physical ERD Example

  19. AIA - Logical ERD Example

  20. AIA - Physical ERD Example

  21. Is Data Modeling Dead? Some reasons for the question: • Failure of enterprise data models? • RAD/Prototyping Techniques? • Object Oriented Analysis & Design?

  22. Is Data Modeling Dead? Open Discussion !!!

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