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DataEd Slides: Conceptual vs. Logical vs. Physical Data Modeling

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About the Webinar

A model is developed for a purpose. Understanding the strengths of each of the three Data Modeling types will prepare you with a more robust analyst toolkit. The program will describe modeling characteristics shared by each modeling type. Using the context of a reverse engineering exercise, delegates will be able to trace model components as they are used in a common data reengineering exercise that is also tied to a Data Governance exercise.

Learning objectives:

  • Understanding the role played by models
  • Differentiate appropriate use among conceptual, logical, and physical data models
  • Understand the rigor of the round-trip data reengineering analyses
  • Apply appropriate use of various Data Modeling types

About the Speaker

Peter Aiken, PhD

Professor of Information Systems, VCU and Founder, Anything Awesome

Peter Aiken, an acknowledged Data Management (DM) authority, is an Associate Professor at Virginia Commonwealth University, past President of DAMA International, and Associate Director of the MIT International Society of Chief Data Officers. For more than 35 years, Peter has learned from working with hundreds of Data Management practices in 30 countries. Among his 10 books are the first on CDOs (the case for data leadership), the first describing the use of monetization data for profit/good, and the first on modern strategic data thinking. International recognition has resulted in an intensive schedule of events worldwide. Peter also hosts the longest-running DM webinar series (hosted by dataversity.net). From 1999 (before Google, before data was big, and before Data Science), he founded Data Blueprint, a consulting firm that helped more than 150 organizations leverage data for profit, improvement, competitive advantage, and operational efficiencies. His latest venture is Anything Awesome.

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