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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.
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.
There are six primary data types in MDX Scalar. Scalar is either a number or a string. It can be specified as a literal, e.g. number 5 or string "OLAP" or it can be returned by an MDX function, e.g. Aggregate (number), UniqueName (string), .Value (number or string) etc. Dimension/Hierarchy. Dimension is a dimension of a cube. A dimension is a ...
As of Oracle Database 11g, the Oracle database optimizer can transparently redirect SQL queries to levels within the OLAP Option cubes. The cubes are managed and can take the place of multi-dimensional materialized views, simplifying Oracle data-warehouse management and speeding up query response.
Cubes provides to an analyst or any application end-user "understandable and natural way of reporting using concept of data Cubes – multidimensional data objects". Cubes was first publicly released in March 2011. The project was originally developed for Public Procurements of Slovakia. [3] Cubes 1.0 was released in September 2014 and ...
Data orientation is the representation of tabular data in a linear memory model such as in-disk or in-memory. The two most common representations are column-oriented (columnar format) and row-oriented (row format). [1] [2] The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical ...
Normalization splits up data to avoid redundancy (duplication) by moving commonly repeating groups of data into new tables. Normalization therefore tends to increase the number of tables that need to be joined in order to perform a given query, but reduces the space required to hold the data and the number of places where it needs to be updated if the data changes.
In statistics, econometrics and related fields, multidimensional analysis (MDA) is a data analysis process that groups data into two categories: data dimensions and measurements. For example, a data set consisting of the number of wins for a single football team at each of several years is a single-dimensional (in this case, longitudinal) data ...
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