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.
Data Modeling for Everyone is for those who:
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
Data Modeling for Everyone provides a solid foundation in the following tools & techniques:
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
"synopsis" may belong to another edition of this title.
This work provides a solid foundation in the following tools and techniques: the different types of data modelling - 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; modelling 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; and graphical data modelling, focusing on the IDEF1X notation.
"About this title" may belong to another edition of this title.
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