Data Warehousing

Analysis Services

Today, organizations need to drive actionable insights to people across the enterprise. Rely on one of the most widely used multidimensional analysis tools in the world, Microsoft SQL Server 2008 R2 Analysis Services, to build comprehensive, enterprise-scale analytic solutions that reach every user through familiar applications.

Key Capabilities
  • Rely on feature-rich, powerful, and easy-to-use online analytical processing (OLAP) and data-mining capabilities.
  • Scale analytical solutions to meet enterprise needs.
  • Enhance productivity with design aids and best practices.
  • Drive actionable insight with help from familiar tools.
  • Consolidate enterprise analysis data and KPIs.

Technical Highlights

Rely on Analysis Services to scale demanding analytical applications that run on millions of records and deliver comprehensive, high-quality BI solutions.

Realize the power of a scalable infrastructure
  • Use dynamic management views for near-real-time resource monitoring and performance tuning.

  • Eliminate processing and storage overhead by sharing a read-only database between several servers.

  • Add global perspective to your solutions.

  • Give users access to localized analytical data in their native language, powerful translation capabilities, and more.

  • Take advantage of the improved Aggregation Designer to optimize OLAP performance.

  • Eliminate unnecessary aggregations through block computation.

  • Enable high-performance “what if” scenarios with the new MOLAP-enabled write-back capabilities.

Increase developer productivity
  • Benefit from using Business Intelligence Development Studio—visual tools that are familiar to developers.

  • Detect design issues early in the development cycle with notifications from best-practice alerts.

  • Accelerate and enhance the development process by using cube, dimension, and attribute designers and wizards to model complex business problems.

  • Use the open architecture to extend solutions by creating plug-in algorithms for data mining.

Improve analytical performance
  • Take advantage of a highly compressed and optimized data cache that is maintained as data in the underlying source databases changes.

  • Use Proactive Caching to provide superb query performance and isolate data source systems.

  • Combine real-time updates with MOLAP-class performance.

Reduce overhead through a scalable backup solution
  • Optimize backup performance easily.

  • Take advantage of a solution that offers performance comparable to that of a file-copy operation.

Additional Information

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