🛢DBMS: Logical Design (Definitions)

 "An implementation-independent design that models the entities, relationships, and attributes in a database." (Microsoft Corporation, "SQL Server 7.0 System Administration Training Kit", 1999)

"An implementation-independent design that models the entities, relationships, and attributes in a database." (Microsoft Corporation, "Microsoft SQL Server 7.0 Data Warehouse Training Kit", 2000)

"The phase of a database design concerned with identifying the relationships among the data elements. Contrast with Physical design." (Ralph Kimball & Margy Ross, "The Data Warehouse Toolkit" 2nd Ed., 2002)

"A part of database design that is concerned with modeling the business requirements and data." (S. Sumathi & S. Esakkirajan, "Fundamentals of Relational Database Management Systems", 2007)

"The abstract design and structure of your relational database." (Robert D Schneider & Darril Gibson, "Microsoft SQL Server 2008 All-in-One Desk Reference For Dummies", 2008)

"The abstract design and structure of your relational database. Focusing on the high-level objects and their interrelationships, this is usually generated during the analysis phase of most projects. It then serves as a guideline for creating the actual implementation of your SQL Server database." (Robert D. Schneider and Darril Gibson, "Microsoft SQL Server 2008 All-In-One Desk Reference For Dummies", 2008)

"The steps in the database life cycle involved with the design of the conceptual data model (schema), schema integration, transformation to SQL tables, and table normalization; the design of a database in terms of how the data is related, but without regard to how it will be stored." (Toby J Teorey, ", Database Modeling and Design" 4th Ed., 2010)

"A stage in the design phase that matches the conceptual design to the requirements of the selected DBMS and is, therefore, software-dependent. It is used to translate the conceptual design into the internal model for a selected database management system, such as DB2, SQL Server, Oracle, IMS, Informix, Access, and Ingress." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)