Table of Contents

What is a Data Model?; Why Do We Need a Data Model?; What Camera Settings Also Apply to a Data Model?; What Are Entities?; What Are Data Elements?; What Are Relationships?; What Are Keys?; What Are Subject Area Models?; What Are Logical Data Models?; What Are Physical Data Models?; Which Templates Can Help with Capturing Requirements?; What is the Data Model Scorecard(R); How Can We Work Effectively with Others?; What is Unstructured Data?; What is UML?; What Are the Top 5 Most Frequently Asked Questions?

About the Author

Steve Hoberman balances the formality and precision of data modeling with the realities of building software systems with severe time, budget, and people constraints. In his consulting and teaching, he focuses on templates, tools, and guidelines to reap the benefits of data modeling with minimal investment. He taught his first data modeling class in 1992 and has educated more than 10,000 people about data modeling and business intelligence techniques since then, spanning every continent except Africa and Antarctica. Steve is the author of seven books on data modeling, including the bestseller Data Modeling Made Simple. He is the founder of the Design Challenges group, inventor of the Data Model Scorecard(R), Conference Chair of the Data Modeling Zone conference, recipient of the 2012 Data Administration Management Association (DAMA) International Professional Achievement Award, and highest rated presenter at Enterprise Data World 2014. Steve can be reached at me@stevehoberman.com, @DataMdlRockStar on Twitter, or through Steve Hoberman on Linked-In.

Reviews

Watch the author describe this informative book in this short video. Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices.