Learn more about On-Line Analytical Processing – OLAP
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.
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.
For further study we recommend the following links.
Please
inform us if you know of a web page that belong
here.
OLAP Reporting Tool extends the
built-in OLAP features in Excel and
makes them easier to work with, especially for
workgroups.
Users can share customized
reports without effort. Either display
a graph or a table or a combination of both.
Choose between all the Excel graph types and
also use the multi-graph feature to display
multiple graphs side by side, compared on any
set of data.
