This paper reviews three online resources that define and explain data modeling, each approaching the subject from a distinct angle. The first resource provides a beginner-friendly introduction to data modeling types and processes. The second uses visual diagrams to compare conceptual, logical, and physical data models. The third is a professional online magazine addressing current trends and enterprise-level concerns in data modeling. Together, the three resources illustrate how data modeling is defined, taught, and applied across different audiences — from students and entry-level IT professionals to experienced enterprise developers.
The following reviews examine three resources — two websites and one online magazine — that define and explain data modeling. Each resource approaches the subject from a different angle, serving audiences that range from entry-level IT students to seasoned enterprise professionals.
Ambler, Scott W. (2011). Data Modeling 101. Agile Data. Retrieved from http://www.agiledata.org/essays/dataModeling101.html
This resource provides an introduction to data modeling with a comprehensive table of contents and easy navigation links to various areas of the article. It clearly defines different types and uses of data modeling, including the three basic styles of data model: conceptual models, logical models, and physical models. Most of the article is devoted to comparing conceptual and logical models, given that these are the most commonly used in agile development contexts.
The resource also provides a step-by-step overview of the general data modeling process, covering the need to: identify entity types; identify attributes; apply naming conventions; identify relationships; apply data model patterns; assign keys; normalize to reduce data redundancy; and denormalize to improve performance.
The intention of the website is instructive. The information is presented in a manner designed to help entry-level IT professionals apply data modeling effectively in their work, and every step is illustrated with charts and examples. Greater attention is given to the types of models used in the everyday life of a developer, and career advice is also offered to the reader: "You should take the opportunity to work with the enterprise architects within your organization — they should be taking an active role on your project, mentoring your project team in the enterprise architecture (if any), mentoring you in modeling and architectural skills, and aiding in your team's modeling and development efforts."
Data modeling — Conceptual, logical, and physical data models. (2012). 1 Key Data. Retrieved from http://www.1keydata.com/datawarehousing/data-modeling-levels.html
"Visual comparison of three data model levels"
"Professional magazine covering enterprise data modeling trends"
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