High-speed analysis can be accomplished by extracting the relational data into a multidimensional format called an OLAP cube; by loading the data to be analyzed into memory; by storing the data in ...

New applications, such as agricultural reports, are emerging. Cubes used for OLAP allow fast data analysis by defining dimensions that define the problem being analysed. It might, for example, consist ...

Multi-dimensional OLAP, actually persistent data structures and access protocols, mostly on disk, but a few hybrid arrangements where the “cubes” were both physical and virtual or transient in memory.

"Kyvos is a solution which brings a new model of online analytical processing (OLAP) to Big Data that allows users to visually create and analyze 'cubes on Hadoop,' " the company said in a news ...

Data from OLTP systems is aggregated and analyzed by online analytical processing (OLAP). OLAP cubes are multidimensional databases that are ideal for applications like data warehouses and online ...

OLAP enables managers ... Figure 1.4 Each dimension is defined by its attributes. After data is loaded in the cube, you can access it with many client applications. Microsoft Excel is one of ...

And unlike "old school" OLAP, which requires such aggregations ... one customer has already migrated over 100TB of data to a single Kyligence cube and that another ported some 1200 IBM Cognos ...

The ‘traditional’ OLAP engine follows a simple paradigm: connect to the data source(s), extract the appropriate data, run through a builder process to create a cube, provide access to the cube.

For example, for OLE DB for OLAP multidimensional data that contains CONTINENT ... to pass an MDX statement to a Microsoft SQL Server Decision Support Services (DSS) Cube. The provider used is the ...

First, you will learn how to set up BI EE metadata over OLAP cubes using a new Analytic Workspace Manager plug-in. Then, you will see how the cube is queried using BI EE Answers.