DataEd Slides: Data Architecture vs. Data Modeling – Compare and Contrast

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About the Webinar

Many are confused when it comes to data. Architecture, models, data – it can seem a bit overwhelming. This program offers a clear explanation of both Data Architecture and Data Modeling. Data Modeling is a primary means of achieving better understanding of specific Data Architecture components. Data Architecture is the sum of the various organizational data models. Both are made more useful by the other. Data models are literally the pages, intersecting Data Architecture and Data Modeling. Any time you are talking architecture, it is important to include the complementary role of engineering.

Engineering must be addressed from both forward and reverse perspectives. Only when working in a coordinated manner can organizations take steps to better understand what they have and what they need to accomplish – employing Data Modeling and Data Architecture to achieve their mission. Data models are required for this coordination, providing the means of verifying integration, the primary documentation, and required input to data systems evolution. Program learning objectives include:

  • Understanding the role played by models
  • Incorporating the interrelated concepts of architecture/engineering
  • What is taught: forward engineering with a goal of building
  • What is also needed: reverse engineering with a goal of understanding
  • How increasing coordination requirements increase design simplicity

About the Speaker

Peter Aiken, PhD

Founding Director, Data Blueprint

Peter Aiken is an acknowledged Data Management (DM) authority. As a practicing data consultant, professor, author, and researcher, he has studied DM for more than 30 years. International recognition has come from assisting more than 150 organizations in 30 countries. He is a dynamic presence at events and author of 10 books and multiple publications, including his latest on Data Strategy. Peter also hosts the longest running webinar series dedicated to DM (hosted by dataversity.net). In 1999, he founded Data Blueprint, a consulting firm that helps organizations leverage data for profit, improvement, competitive advantage, and operational efficiencies. He is also Associate Professor of Information Systems at Virginia Commonwealth University (VCU), past President of the International Data Management Association (DAMA-I), and Associate Director of the MIT International Society of Chief Data Officers.

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