Ranet UILibrary.OLAP for Windows

Name: Ranet UILibrary.OLAP
Rating: 4 (1 reviews)
Author: Galaktikasoft

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Developer’s Description

By Galaktikasoft

Provide an open source set of data visualization controls.

Components library Ranet.UILibrary.OLAP is intended for creating full-featured business intelligence applications (RIA, Rich Internet Applications) based on the Microsoft SQL Server Analysis Services platform. Visual elements that are included with the Ranet.UILibrary.OLAP library offer strong functionality and excellent design. This intuitive and easy-to-master tool does not require technical knowledge or programming skills from the user. It can meet business analysis requirements of the most demanding users. Unlimited analytical possibilities offered by Ranet.UILibrary.OLAP library components enable the user to view the data from various angles. They help reveal business development trends that could have gone unnoticed or seemed of no importance. The visual elements included with the Ranet.UILibrary.OLAP library permit to create interactive reports of any complexity level based on the data of the Microsoft Analysis Services OLAP cubes. Depending on the skill and professional level of the user, one can build an interactive report simply by dragging and dropping the cube metadata elements to the filter area, rows, columns of the summary table. Alternatively, it is possible to prepare a complex MDX query, using maximum capabilities of the MDX language, in order to achieve the most efficient solution for the report. The Drill Down, Drill Up, and Drill Through functions give the user the maximum possibilities for detailed data analysis: - Going into different data levels, from summary to detailed data (the hierarchy of the dimension determines the drill down ways);- Possibility to go down to the detailed data (Drill Down) by expanding the hierarchy nodes or going back to the summary data (Drill Up);- Analyzing the actual data behind the aggregate indicator (Drill Through);Flexible filter configuration parameters permit data search and data filtering based on most diverse criteria.