Search results
Results from the WOW.Com Content Network
An example of an OLAP cube. An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [2] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.
Apache Kylin is a distributed data store for OLAP queries originally developed by eBay. Cubes (OLAP server) is another lightweight open-source toolkit implementation of OLAP functionality in the Python programming language with built-in ROLAP. ClickHouse is a fairly new column-oriented DBMS focusing on fast processing and response times.
In computer programming contexts, a data cube (or datacube) is a multi-dimensional ("n-D") array of values. Typically, the term data cube is applied in contexts where these arrays are massively larger than the hosting computer's main memory; examples include multi-terabyte/petabyte data warehouses and time series of image data.
Multidimensional Expressions (MDX) is a query language for online analytical processing (OLAP) using a database management system. Much like SQL, it is a query language for OLAP cubes. [1] It is also a calculation language, with syntax similar to spreadsheet formulae.
For the special case of sparse data, OLAP data cubes are well established; they store cell values together with their location – an adequate compression technique in face of the few locations carrying valid information at all – and operate with SQL on them. As this technique does not scale in density, standard databases are not used today ...
A dimension is a finite set of elements, or members, that identify business data, e.g., time periods, products, areas or regions, line items, etc. Cubes are built using any number of dimensions. A cube is a collection of cells, each of which is identified by a tuple of elements, one from each dimension of the cube.
Datawatch's technology relies on in-memory OLAP (Online Analytical Processing) cubes, which are displayed through a series of visualizations including treemaps.This allows the user to load data, select variables and hierarchical structures, and navigate through the resultant visualization, filtering, zooming and drilling (sometimes called slicing and dicing), to identify outliers, correlations ...
OLAP Services supported MOLAP, ROLAP, and HOLAP architectures, and it used OLE DB for OLAP as the client access API and MDX as a query language. It could work in client-server mode or offline mode with local cube files. [3] In 2000, Microsoft released Analysis Services 2000. It was renamed from "OLAP Services" due to the inclusion of data ...