"This book covers key topics such as gathering requirements, modeling requirements with use cases, testing the system, building entity-relationship models, building class models in UML with patterns of data modeling and software quality attributes, and use case modeling. It also includes case studies of relational and object-relational database schema design"--

The Software Principles of Design for Data Modeling, written by Debabrata Samanta of Rochester Institute of Technology in Kosovo, offers a practical and comprehensive solution to the challenges of designing effective software architecture for data modeling. This book covers key topics such as gathering requirements, modeling requirements with use cases, testing the system, building entity-relationship models, building class models in UML with patterns of data modeling and software quality attributes, and use case modeling. It also includes case studies of relational and object-relational database schema design. The unique approach of this book lies in its unifying method for designing software architecture for data modeling. It addresses specific design issues for various types of software systems, including object-oriented, client/server, service-oriented, component-based, real-time, and software product line architectures. With its practical guidance, standard method for modeling requirements and analysis, and comprehensive coverage of key topics and case studies, this book is a must-read for anyone interested in designing effective software architecture for data modeling, whether you are an academic scholar or a professional in the field.

Typically, analysis, development, and database teams work for different business units, and use different design notations. With UML and the Rational Unified Process (RUP), however, they can unify their efforts -- eliminating time-consuming, error-prone translations, and accelerating software to market. In this book, two data modeling specialists from Rational Software Corporation show exactly how to model data with UML and RUP, presenting proven processes and start-to-finish case studies. The book utilizes a running case study to bring together the entire process of data modeling with UML. Each chapter dissects a different stage of the data modeling process, from requirements through implementation. For each stage, the authors cover workflow and participants' roles, key concepts, proven approach, practical design techniques, and more. Along the way, the authors demonstrate how integrating data modeling into a unified software design process not only saves time and money, but gives all team members a far clearer understanding of the impact of potential changes. The book includes a detailed glossary, as well as appendices that present essential Use Case Models and descriptions. For all software team members: managers, team leaders, systems and data analysts, architects, developers, database designers, and others involved in building database applications for the enterprise.

This advanced guide for software engineers is intended to provide useful building blocks for the design of highly complex software. The authors have devised a small, integrated set of software design principles, along with practical models of the principles at work. Includes solutions for simultaneous execution in different configurations and operating systems.

"Domain-Driven Design" incorporates numerous examples in Java-case studies taken from actual projects that illustrate the application of domain-driven design to real-world software development.

Until now, almost all books on logical database design focused exclusively on relational design. However, modern database management systems have added powerful features that have driven a movement away from truly normalized database design. Logical Database Design Principles reflects these recent changes. The book begins by covering traditional logical design principles, followed by an analysis of the normalizing and modeling of data. It then examines designing for specific purposes, such as object-oriented databases, online transaction processing (OLTP), and data warehouses. As the text progresses, it moves from the purely logical into some physical design, as determined by how the features of modern databases are implemented. Because this is a logical-design book, the authors attempt to make the examples database-neutral. Because various vendors implement features in different ways, this volume sometimes offers examples from a specific database management system. When necessary, it highlights a specific application, clearly demonstrating the concept being discussed.