On-Line Analytical Processing – OLAP
– is a category of applications and technologies
for collecting, managing, processing and
presenting multidimensional data for analysis
and management purposes.
OLAP uses a multidimensional view of aggregate
data to provide quick access to strategic
information for further analysis.
OLAP allows fast and efficient analysis
of data by turning raw data into information
that can be understood by users and manipulated
in various ways.
OLAP applications require multidimensional
views of data, and usually, calculation-intensive
capabilities and time intelligence.
OLAP is computer processing that enables
a user to easily and selectively extract
and view data from different points of view.
Example: a user can request that data should
be analyzed to display a spreadsheet showing
all of a company's beach ball products sold
in Florida in the month of July, compare
revenue figures with those for the same
products in September, and then see a comparison
of other product sales in Florida in the
same time period.
To facilitate this kind of analysis, OLAP
data is stored in a multi-dimensional database. |
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OLAP can be used for data mining or
for the discovery of previously undiscerned
relationships between data items.
An OLAP database does not need to
be as large as a data warehouse, since not
all transactional data is needed for trend
analysis. Using Open Database Connectivity
(ODBC), data can be imported from existing
relational databases to create a multidimensional
database for OLAP.
OLAP functionality is characterized by dynamic
multi-dimensional analysis of consolidated
enterprise data supporting end user analytical
and navigational activities. The objective
of multi-dimensional analysis is for end
users to gain insight into the meaning contained
in databases.
The multi-dimensional approach to analysis
aligns the data content with the analyst's
mental model, which helps avoiding confusion
and erroneous interpretations. It also eases
navigating the database, screening for a
particular subset of data, asking for the
data in a particular orientation and defining
analytical calculations.
Since the data is physically stored in a
multi-dimensional structure, the speed of
these operations is many times faster and
more consistent than is possible in other
database structures. This combination of
simplicity and speed is one of the key benefits
of multi-dimensional analysis. |
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