BOOKS - OS AND DB - Data Modeling Made Simple with Embarcadero ER/Studio Data Archite...
Data Modeling Made Simple with Embarcadero ER/Studio Data Architect Adapting to Agile Data Modeling in a Big Data World - Hoberman Steve 2015 PDF Technics Publications BOOKS OS AND DB
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Data Modeling Made Simple with Embarcadero ER/Studio Data Architect Adapting to Agile Data Modeling in a Big Data World
Author: Hoberman Steve
Year: 2015
Number of pages: 350
Format: PDF
File size: 13 MB
Language: ENG

This book contains four sections: Section I introduces data modeling and the ERStudio landscape. Learn why data modeling is so critical to software development and even more importantly, why data modeling is so critical to understanding the business. You will learn about the newest features in ERStudio (including features on big data and agile), and the ERStudio environment. By the end of this section, you will have created and saved your first data model in ERStudio and be ready to start modeling in Section II! Section II explains all of the symbols and text on a data model, including entities, attributes, relationships, domains, and keys. By the time you finish this section, you will be able to ‘read’ a data model of any size or complexity, and create a complete data model in ERStudio. Section III explores the three different levels of models: conceptual, logical, and physical. A conceptual data model (CDM) represents a business need within a defined scope. The logical data model (LDM) represents a detailed business solution, capturing the business requirements without complicating the model with implementation concerns such as software and hardware. The physical data model (PDM) represents a detailed technical solution. The PDM is the logical data model compromised often to improve performance or usability. The PDM makes up for deficiencies in our technology. By the end of this section you will be able to create conceptual, logical, and physical data models in ERStudio.Section IV discusses additional features of ERStudio. These features include data dictionary, data lineage, automating tasks, repository and portal, exporting and reporting, naming standards, and compare and merge functionality.

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