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 ...

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.

Multidimensional analysis, or the use of pre-computed OLAP cubes, used to be a primary method for quickly obtaining useful information from reams of data, but has largely fallen out of favor in the ...

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 ...

Many tools exist to help management with analysis, modelling and reporting in order to realise the value in their data. Pitram’s OLAP (Online Analytical Processing) tool is an example of this ...