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Data Modeling Made Simple with Embarcadero ER/Studio Data Architect

- Adapting to Agile Data Modeling in a Big Data World
Af: Steve Hoberman Engelsk Paperback

Data Modeling Made Simple with Embarcadero ER/Studio Data Architect

- Adapting to Agile Data Modeling in a Big Data World
Af: Steve Hoberman Engelsk Paperback
Tjek vores konkurrenters priser
Build a working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. This second edition includes numerous updates and new sections including an overview of ER/Studio''s support for agile development, as well as a description of some of ER/Studio''s newer features for NoSQL, such as MongoDB''s containment structure. You will build many ER/Studio data models along the way, applying best practices to master these ten objectives: 1. Know why a data model is needed and which ER/Studio models are the most appropriate for each situation. 2. Understand each component on the data model and how to represent and create them in ER/Studio. 3. Know how to leverage ER/Studio''s latest features including those assisting agile teams and forward and reverse engineering of NoSQL databases. 4. Know how to apply all the foundational features of ER/Studio. 5. Be able to build relational and dimensional conceptual, logical, and physical data models in ER/Studio. 6. Be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design. 7. Improve data model quality and impact analysis results by leveraging ER/Studio''s lineage functionality and compare/merge utility. 8. Be able to apply ER/Studio''s data dictionary features 9. Learn ways of sharing the data model through reporting and through exporting the model in a variety of formats. 10.Leverage ER/Studio''s naming functionality to improve naming consistency, including the new Automatic Naming Translation feature. This book contains four sections: Section I introduces data modeling and the ER/Studio 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 ER/Studio (including features on big data and agile), and the ER/Studio environment. By the end of this section, you will have created and saved your first data model in ER/Studio 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 ER/Studio. 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 ER/Studio. Section IV discusses additional features of ER/Studio. These features include data dictionary, data lineage, automating tasks, repository and portal, exporting and reporting, naming standards, and compare and merge functionality.
Tjek vores konkurrenters priser
Normalpris
kr 640
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser
Build a working knowledge of data modeling concepts and best practices, along with how to apply these principles with ER/Studio. This second edition includes numerous updates and new sections including an overview of ER/Studio''s support for agile development, as well as a description of some of ER/Studio''s newer features for NoSQL, such as MongoDB''s containment structure. You will build many ER/Studio data models along the way, applying best practices to master these ten objectives: 1. Know why a data model is needed and which ER/Studio models are the most appropriate for each situation. 2. Understand each component on the data model and how to represent and create them in ER/Studio. 3. Know how to leverage ER/Studio''s latest features including those assisting agile teams and forward and reverse engineering of NoSQL databases. 4. Know how to apply all the foundational features of ER/Studio. 5. Be able to build relational and dimensional conceptual, logical, and physical data models in ER/Studio. 6. Be able to apply techniques such as indexing, transforms, and forward engineering to turn a logical data model into an efficient physical design. 7. Improve data model quality and impact analysis results by leveraging ER/Studio''s lineage functionality and compare/merge utility. 8. Be able to apply ER/Studio''s data dictionary features 9. Learn ways of sharing the data model through reporting and through exporting the model in a variety of formats. 10.Leverage ER/Studio''s naming functionality to improve naming consistency, including the new Automatic Naming Translation feature. This book contains four sections: Section I introduces data modeling and the ER/Studio 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 ER/Studio (including features on big data and agile), and the ER/Studio environment. By the end of this section, you will have created and saved your first data model in ER/Studio 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 ER/Studio. 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 ER/Studio. Section IV discusses additional features of ER/Studio. These features include data dictionary, data lineage, automating tasks, repository and portal, exporting and reporting, naming standards, and compare and merge functionality.
Produktdetaljer
Sprog: Engelsk
Sider: 350
ISBN-13: 9781634620925
Indbinding: Paperback
Udgave:
ISBN-10: 1634620925
Kategori: Databaser
Udg. Dato: 1 okt 2015
Længde: 24mm
Bredde: 191mm
Højde: 237mm
Forlag: Technics Publications LLC
Oplagsdato: 1 okt 2015
Forfatter(e): Steve Hoberman
Forfatter(e) Steve Hoberman


Kategori Databaser


ISBN-13 9781634620925


Sprog Engelsk


Indbinding Paperback


Sider 350


Udgave


Længde 24mm


Bredde 191mm


Højde 237mm


Udg. Dato 1 okt 2015


Oplagsdato 1 okt 2015


Forlag Technics Publications LLC

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