Database enterprise manager
- System study
- Feasibility study, Existing system and Proposed system
- Language specification
- Features of ASP.NET
- Features of MS-access 2000
- System design
- Input and output design
- System testing and maintenance
- Unit testing, Integration testing and Validation testing
- System implementation
- Scope for future development
- Bibliography and Appendix (Screen shots, Data table structure and Sample coding
- Hardware specification
- Processor: Pentium III 766 MHz, RAM: 128 MD SD RAM, Monitor: 15 inch color, Hard disk: 20 GB
- Floppy drive: 1.44 MB, CD drive: LG 52X
- Software specification
- Operating system: Windows 2000 professional, Environment: Visual studio .NET 2005
- .NET framework: Version 2.0, Language: C#.NET
- Web technology: Active server pages.NET, Web server: Internet information server 5.0
- Back end: MS-access 2000
- Reports: Web form data grid control
The project titled ?Database Enterprise Manger? is designed using Active Server Pages .NET with Microsoft Visual Studio.Net 2005 as front end and Microsoft SQL Server 2000 as back end which works in .Net framework version 2.0. The coding language used is VB .Net.
The system ?Database Enterprise Manger? is developed to work in the front-end as enterprise database management system. In this we can create/delete database. User can create the table/triggers/view/stored procedures and set Authentication for the database and tables.
The new Database Enterprise Manager tool has been designed to better expose the simplicity and self-healing capabilities built in the product. Matisse Database Enterprise Manager makes administrators more productive by ensuring the optimum level of performance all the time and thus removing tedious administration tasks from DBAs daily routines.
Matisse Database Enterprise Manager simplifies the transition from relational products to Matisse by using familiar relational terminology to present database objects. The Database Enterprise Manager tool promotes Matisse superior technology for modeling real-world applications, and for processing large volumes of data as well as for analyzing and reporting on complex business data.