RadarCube ASP.NET OLAP Control for MS AS: Fast Interactive Data Visualization

Build Dynamic Dashboards with RadarCube ASP.NET OLAP Control for MS AS

Overview

RadarCube is an ASP.NET OLAP visualization control designed to connect to Microsoft Analysis Services (MS AS) and render multidimensional data in interactive dashboard components. It lets developers create dynamic, drillable dashboards that display KPIs, slices, and aggregations from OLAP cubes without heavy custom visualization code.

Key Capabilities

• Live OLAP connectivity: Directly query MS Analysis Services cubes (MDX/DAX) to fetch measures and dimensions.
• Interactive drilldown: Users can expand/collapse hierarchies, drill into dimensions, and apply context-aware filters.
• Multiple visualizations: Support for grids, charts, pivot tables, and radar/spider charts tailored for multidimensional data.
• Client-side responsiveness: AJAX and client-rendering reduce server load and provide near-real-time interactivity.
• Customization: Templates, styling, and event hooks let developers match dashboards to application themes and behaviors.
• Export & printing: Export views to Excel, PDF, or image formats for sharing and reporting.

Typical Architecture

1. ASP.NET web application hosts RadarCube controls.
2. RadarCube connects to MS AS via a secure connection string and executes MDX/DAX queries.
3. Server-side processing handles authentication and large aggregations; client-side control renders and manages interactions.
4. Optional caching layer to store query results and improve responsiveness.

Implementation Steps (concise)

1. Add RadarCube ASP.NET control to your project (NuGet/package or DLL).
2. Configure connection string to MS Analysis Services and set authentication.
3. Define cube queries (MDX/DAX) or bind controls to cube metadata (measures/dimensions).
4. Place RadarCube controls on ASPX/CSHTML pages and map UI events (drill, filter, sort).
5. Implement server-side handlers for heavy queries and caching.
6. Style templates and enable export features.

Best Practices

• Use server-side caching for costly MDX queries to speed repeated views.
• Limit initial result sets and enable progressive loading to avoid long waits.
• Secure connections: use Windows authentication or service accounts with least privilege.
• Pre-aggregate common measures in the cube to reduce query complexity.
• Provide intuitive drill paths and breadcrumbs to keep users oriented.

When to Use

• Enterprise dashboards tied to OLAP cubes where multidimensional analysis, slicing, and drilldown are primary needs.
• Applications requiring rapid development of BI dashboards with built-in OLAP-aware visualizations.

Alternatives to Consider

• Power BI (for full-featured BI platform and cloud integration)
• DevExpress/XtraPivotGrid or Telerik OLAP controls (other .NET OLAP UI components)