One of the advantages
of OLAP is how data and its relationships are stored and accessed.
OLAP systems house data in structures that are readily available for
detailed queries and analytics. Cubes are central to the OLAP storage
process.
A cube is a set of data
that is organized and structured in a hierarchical, multidimensional
arrangement. The cube is usually derived from a subset of a data warehouse.
Unlike relational databases that use two-dimensional data structures
(often in the form of columns and rows in a spreadsheet), OLAP cubes
are logical, multidimensional models that can have numerous dimensions
and levels of data. Also, an organization typically has different
cubes for different types of data.
One of the challenges
of OLAP cube data storage and retrieval is the growth of data and
how that growth affects the number of dimensions and levels in a cube
hierarchy. As the number of dimensions increases over time, so does
the number of data cells on an exponential scale. To maintain the
efficiency and speed of the OLAP queries, the cube data is often presummarized
into various consolidations and subtotals (aggregations).
Note: The SAS OLAP Server
term cube is synonymous with the terms hyper-cube and multi-cube.