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Supported data models (conceptual, logical, physical) Supported notations Forward engineering Reverse engineering Model/database comparison and synchronization Teamwork/repository Database Workbench: Conceptual, logical, physical IE (Crow’s foot) Yes Yes Update database and/or update model No Enterprise Architect
Dedicated to modeling and testing of communicating systems. Based on ITU-T Z.109 UML profile, SDL-RT, SDL. The model can be simulated and can be exported to model checking tools. Full testing environment integrated based on TTCN-3. Prosa UML Modeller: Yes Yes Open modelbase Yes C++ Java, C#, SQL DDL and SQL queries
Data modeling techniques and methodologies are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The use of data modeling standards is strongly recommended for all projects requiring a standard means of defining and analyzing data within an organization, e.g., using data modeling:
The Toolkit for Conceptual Modeling (TCM) is a collection of software tools to present specifications of software systems in the form of diagrams, tables, trees, and the like. TCM offers editors for techniques used in Structured Analysis as well as editors for object-oriented (UML) techniques.
Obeo & CEA List Web 2023 2024.11 [18] Yes Eclipse Public License Java System Architect: UNICOM Global: Windows 1988 & 2005 (for SA XT web version) 2022-10-18 No Commercial C++ and Visual Basic; JavaScript for SA XT web sister product System Architecture Modeler Ansys Windows, Linux, macOS July 2024 - 2024 R2 February 2025 - 2025 R1 No ...
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.
A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration , for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems.
Data Flow Modeling examines processes (activities that transform data from one form to another), data stores (the holding areas for data), external entities (what sends data into a system or receives data from a system), and data flows (routes by which data can flow). Entity Event Modelling A two-stranded process: Entity Behavior Modelling ...