ramsetcube R10
Using RAMSETCUBE you could manage the metadata of a Data Warehouse also for Mondrian(TM) projects, with a real flexible approach, reducing cycle times for changes, through a secure and user friendly environment.
Last update
30 Nov. 2010
Licence
Free
OS Support
Windows 2000
Downloads
Total: 535 | Last week: 2
Ranking
#457 in
Accounting & Billing Software
Publisher
Eng. Matteo Taverna
Screenshots of ramsetcube
ramsetcube Publisher's Description
Using RAMSETCUBE you could manage the metadata of a Data Warehouse also for Mondrian-Pentaho(TM) projects, with a real flexible approach, reducing cycle times for changes, through a secure and user friendly environment. The cube designer techniques offered by RamsetCube permit to manage all the areas of a project maintaining a clear and full vision of relations between objects.
Metadata can be structured by creating or importing tables and relations. In the first case Ramsetcube will send the necessary sql queries against the database, in the second case a logical model will be created to track data. The two criteria can coexist in the same project. During definition of entities, Ramsetcube provides to set up "snowflake" and "star" schemas to be used in cubes. This depends on how data are structured in your DW. Tables with a field code and one to one relations can be defined by the logical model without using trees. This approach makes void the use of hierarchical structures where not essential. As far as concerned time dimensions, they are created just by assigning flags. The role of a level in time dimension is indicated in the XML, due to MDX functions. Trees represent hierarchical models that can be adopted by many cubes at the same time. This is different from other conceptions by which it’s necessary to declare hierarchies for each cube. A cube can also be related with a branch of a tree. This reduce redundancy of duplicated structures. Aggregate tables are built in the same logical object and related to their cube by using a matrix. This allow you to define "lost" and "collapsed" dimensions in a simple and intuitive way, reaching synthesis and control over the project.
Metadata can be structured by creating or importing tables and relations. In the first case Ramsetcube will send the necessary sql queries against the database, in the second case a logical model will be created to track data. The two criteria can coexist in the same project. During definition of entities, Ramsetcube provides to set up "snowflake" and "star" schemas to be used in cubes. This depends on how data are structured in your DW. Tables with a field code and one to one relations can be defined by the logical model without using trees. This approach makes void the use of hierarchical structures where not essential. As far as concerned time dimensions, they are created just by assigning flags. The role of a level in time dimension is indicated in the XML, due to MDX functions. Trees represent hierarchical models that can be adopted by many cubes at the same time. This is different from other conceptions by which it’s necessary to declare hierarchies for each cube. A cube can also be related with a branch of a tree. This reduce redundancy of duplicated structures. Aggregate tables are built in the same logical object and related to their cube by using a matrix. This allow you to define "lost" and "collapsed" dimensions in a simple and intuitive way, reaching synthesis and control over the project.
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