Distributed Data Applications with ASP.NET

This book concentrates on the use of ASP.NET 1.1 and Visual Studio 2003 to build applications for Internet or intranet use, and looks at the possibilities that rich clients bring to both application design and a better user experience. The book itself focuses on n-tier architecture design and the way it can be coded.

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ASP.NET is a huge advance from previous incarnations of ASP, with one of its goals being pure HTML output that achieves maximum cross-browser compatibility. The server-side event architecture tends to engender this approach, but amid the first flush of excitement its often forgotten that theres still a place for rich clients and handling data in a multitude of places. Distributed data-driven applications arent new, but the range of possibilities and ease of development have both increased with the introduction of .NET.


This book approaches data management and data applications from several different points of view:




Understanding the new .NET data management philosophy for both relational and XML data
Grasping the different techniques that it encompasses and how they relate to real-world requirements
Exploring the application architecture and design implications of the .NET data management classes
Designing distributed data-driven ASP.NET applications that benefit from the new data management techniques
Examining the rich-client philosophy and how .NET can be used to bring this about
Demonstrating how easy it is to take advantage of several different types of client devices, providing the best user experience possible for each one





Many books describe the basic techniques for working with data in ASP.NET. However, this book goes not just a step further, but in fact takes you on a complete journey by exploring how to provide the user with the best possible client-side experience when working with data. It also focuses on the server-side design and development process, such as using the n-tier architecture in your applications, and implementing specific techniques, such as correctly managing updates to a data store by multiple concurrent users.