Create consistent OLAP cubes using an integrated ETL process. Say no to plagiarism. Get a Custom Essay on “Why Violent Video Games Should Not Be Banned”? Get an original essay Through a simplified ETL process, SAS OLAP Server makes it easy to create coherent OLAP cubes from disparate systems. Integrated metadata ensures consistent information is provided across the enterprise and allows IT to quickly justify data integrity. Quickly populate your BI applications with stable, summarized data. SAS OLAP Server quickly delivers insights to business intelligence applications, regardless of the amount of underlying data. Summarizing data at multiple levels of detail before storing it provides the summarized data that business intelligence applications need without the need for additional “on-the-fly” processing. Free IT from constantly creating ad hoc reports and data summaries. Because summarized data is organized by industry, users can get the reports they need without involving IT, freeing IT from the constant work of creating reports and summarizing data. Industrial-grade multidimensional database: designed to manage large volumes of business intelligence data. Supports multidimensional (MOLAP) and hybrid datastore (HOLAP) formats. Routines allow SAS procedures to query the SAS OLAP server using SQLPass-Through with access from multidimensional data to the underlying detailed data. Native support for open industry standards: OLE DB for OLAP. Fully compliant implementation of the MDX query language for communicating with third-party clients. Thanks to the open architecture of SAS software, cubes can be displayed via the web, via Microsoft Excel as pivot tables, as well as via SAS or other standards-based browsers. Fast query processing: Multithreaded query engine. Data can be distributed across multiple disk systems, providing parallel read access for query threads. Cluster management for load-balanced servers. Easy-to-use GUIs for creating and maintaining OLAP cubes: Included with SAS OLAP Server, SAS OLAP Cube Studio makes it easy to define dimensions and data aggregations. SAS OLAP Cube Studio is integrated with SAS Data Integration Studio so you can create cubes from cleaned data sources and load them for later use and updating. The Java-based wizard makes it easy to design, create, update and tune OLAP cubes. Create a set of dimensions once, then share them with other cubes, providing consistent hierarchies and saving system resources. Update the bundle and apply it to shared cubes. Optimizing summarized data to conserve system resources: Infrequently accessed data can be stored in a compressed format. Frequently queried data can be cached in memory for a faster access. Dimensions, hierarchies and metrics (metadata) are stored in the cube itself, while the data remains in the database and is only queried at runtime, reducing data duplication and the processing time of the cube. Centralized metadata with security credentials preserved during drill-through: All metadata is stored in a single, open location. – the SAS metadata server. SAS OLAP Server is.