Data Warehousing

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.

Use the richness of a single Unified Dimensional Model (UDM) to accommodate analytical needs ranging from multidimensional analysis and reporting to predictive analysis—all in one solution.

Consolidate enterprise analysis data

• Combine the flexibility and richness of the relational reporting model with the performance of the OLAP model.

• Provide one consolidated business view for relational and multidimensional data that includes business entities, business logic, calculations, and metrics.

• Employ business intelligence (BI) wizards so that all users can effectively model BI problems.

Manage key metrics centrally

• Define, store, and manage key performance indicators (KPIs) from across the enterprise in a centralized repository.

• Enable business users to access centrally stored KPIs through familiar Microsoft Office applications.

Perform predictive analysis

• Offer analytical capabilities that enable users to learn from large volumes of historical data, perform predictive analysis, and identify patterns and business trends.

• Extend the predictive analysis capabilities by using an enhanced data-mining engine and improved algorithms.

• Rely on powerful data-mining capabilities from the Microsoft .NET Framework and data-mining viewers.

Deliver insights widely through tight integration with Microsoft Office and by taking advantage of an open, extensible, embeddable architecture.

Benefit from interoperability with Microsoft Office

• Enable business users to access multidimensional data directly from within Microsoft Excel.

• Empower business users to effortlessly explore the data they need on demand.

• Enjoy the power of the predictive and sophisticated analytical capabilities of data mining directly from Excel by using Data Mining Add-Ins.

Deliver pervasive business insight

• Integrate with Microsoft SharePoint Server for performance management capabilities including monitoring, analysis, and planning.

• Enable collaboration on centralized analytical data by taking advantage of close integration with SharePoint Server.

• Benefit from the applications that hundreds of partners have built on top of Analysis Services.

Extend analysis with web services

• Develop new applications that integrate analytical capabilities with operations in real time.

• Use XML for Analysis to expose data and configure client applications to automatically be a web service.

• Support tools that work with Analysis Services on OLE DB for OLAP, ADOMD, and ADOMD.NET.