Data Modeling is about gathering, documenting, and communicating the elements and structure of business information. What begins as a conceptual interplay of logical data units, through the application of relational theory, becomes the basis for creating a physical database design. Data Modeling is a core skill for data professionals, and is a full time job for a small but growing number of IT practitioners. It is a crucial stage prior to good quality relational database design.

• Have no previous data modeling experience
• Want to understand the role of the data modeler in database design
• Need to know how to capture the essence of a system but don't know where to start
• Want more than just the theory and learn best from real world experience
• Require a book before other data design books - helping you develop a logical model rather than assuming one exists that needs to be implemented in a database

• The different types of data modeling - enterprise, transactional, and dimensional
• The stages of analysis - developing conceptual, logical, and physical models
• What to do if you need to work with existing systems - reverse engineering and forensic analysis
• General principles for converting logical models to physical ones
• Modeling scope - focusing on what's important but allowing for future development of your model
• Defining detail - entity relationship (E/R), key based, and fully attributed models
• Documenting your understanding of the business in the model
• Graphical data modeling, focusing on the IDEF1X notation

Contents

• Data Modeling : an Overview
• Relational Modeling
• Introduction to Relational Theory
• Levels of Analysis
• How Data Models Fit Into Projects
• Building a Conceptual Model
• Building a Logical Model
• Transformation = Logical to Physical
• Designing Only a Physical Model
• Dimensional Data Modeling
• Reverse Engineering a Data Model
• Communication with the Model
• Further Data Analysis
• Meta Data Modeling
• Data Modeling Working Practice