DB2 DPF lets you partition your database across multiple servers or within a large SMP server, which is ideal for Online Analytical Processing ( OLAP ) workloads.

Ad hoc querying / reporting is a business intelligence subtopic, along with OLAP, data warehousing, data mining and other tools.

In computing, online analytical processing, or OLAP (), is an approach to swiftly answer multi-dimensional analytical ( MDA ) queries.

Slicing and dicing is a feature whereby users can take out ( slicing ) a specific set of data of the OLAP cube and view ( dicing ) the slices from different viewpoints.

The core of any OLAP system is an OLAP cube ( also called a ' multidimensional cube ' or a hypercube ).

The usual interface to manipulate an OLAP cube is a matrix interface like Pivot tables in a spreadsheet program, which performs projection operations along the dimensions, such as aggregation or averaging.

Multidimensional structure is quite popular for analytical databases that use online analytical processing ( OLAP ) applications ( O ’ Brien & Marakas, 2009 ).

The most important mechanism in OLAP which allows it to achieve such performance is the use of aggregations.

The objective of view selection is typically to minimize the average time to answer OLAP queries, although some studies also minimize the update time.

' MOLAP ' is the ' classic ' form of OLAP and is sometimes referred to as just OLAP.

There is no clear agreement across the industry as to what constitutes " Hybrid OLAP ", except that a database will divide data between relational and specialized storage.

Below is a list of top OLAP vendors in 2006, with figures in millions of US Dollars.

* MDX is a query language for OLAP databases ;

An OLAP cube is an array of data that is understood in terms of its 0 or more dimensions.

OLAP is an acronym for online analytical processing.

OLAP is a computer-based technique for analyzing business data in the search for business intelligence.

OLAP data is typically stored in a star schema or snowflake schema in a relational data warehouse or in a special-purpose data management system.

In database theory, an OLAP cube is an abstract representation of a projection of an RDBMS relation.

* Multidimensional Expressions, a query language for OLAP databases, much like SQL is a query language for relational databases

MDX was first introduced as part of the OLE DB for OLAP specification in 1997 from Microsoft.

From DSS, data warehouses, Executive Information Systems, OLAP and business intelligence came into focus beginning in the late 80s.

Thomas Davenport has argued that business intelligence should be divided into querying, reporting, OLAP, an " alerts " tool, and business analytics.

Typical applications of OLAP include business reporting for sales, marketing, management reporting, business process management ( BPM ), budgeting and forecasting, financial reporting and similar areas, with new applications coming up, such as agriculture.

The Holos Language was a very broad language in that it covered a wide range of statements and concepts, including the reporting system, business rules, OLAP data, SQL data ( using the Embedded SQL syntax within the hosting HL ), device properties, analysis, forecasting, and data mining.

Crystal Analysis ( a. k. a. Crystal Analysis Professional ) is an On Line Analytical Processing ( OLAP ) application for analysing business data originally developed by Seagate Software.

When creating a data warehouse, a business analyst looks at the Representation Terms to quickly find the dimensions and measures of a subject matter in order to build OLAP cubes.

In database systems, aggregations ( see e. g. OLAP aggregation and Business intelligence systems ) result in transforming original data tables ( often called information systems ) into the tables with different semantics of rows and columns, wherein the rows correspond to the groups ( granules ) of original tuples and the columns express aggregated information about original values within each of the groups.

Unlike relational databases, which had SQL as the standard query language, and widespread APIs such as ODBC, JDBC and OLEDB, there was no such unification in the OLAP world for a long time.

The first real standard API was OLE DB for OLAP specification from Microsoft which appeared in 1997 and introduced the MDX query language.

In 2001 Microsoft and Hyperion announced the XML for Analysis specification, which was endorsed by most of the OLAP vendors.

The first product that performed OLAP queries was Express, which was released in 1970 ( and acquired by Oracle in 1995 from Information Resources ).

In 1998, Microsoft released its first OLAP Server-Microsoft Analysis Services, which drove wide adoption of OLAP technology and moved it into mainstream.

OLAP reporting technologies have allowed faster generation of new reports which analyze the data.

Many commercial OLAP tools now use a " Hybrid OLAP " ( HOLAP ) approach, which allows the model designer to decide which portion of the data will be stored in MOLAP.

The undesirable trade-off between additional ETL cost and slow query performance has ensured that most commercial OLAP tools now use a " Hybrid OLAP " ( HOLAP ) approach, which allows the model designer to decide which portion of the data will be stored in MOLAP and which portion in ROLAP.

HOLAP ( Hybrid Online Analytical Processing ) is a combination of ROLAP ( Relational OLAP ) and MOLAP ( Multidimensional OLAP ) which are other possible implementations of OLAP.

The 2007 version has 14 OLAP cubes which can be used to do Data Analysis with.

SAS is also the first to release OLE-DB for OLAP and releases HOLAP solution.

The first product to provide HOLAP storage was Holos, but the technology also became available in other commercial products such as Microsoft Analysis Services, Oracle Database OLAP Option, MicroStrategy and SAP AG BI Accelerator.

Until late 2005 IBM also marketed the product — as DB2 OLAP Server.

It has been claimed that for complex queries OLAP cubes can produce an answer in around 0. 1 % of the time required for the same query on OLTP relational data.

Modern decision, and classical statistical databases are often closer to the relational model than the multidimensional model commonly used in OLAP systems today.

Some companies select ROLAP because they intend to re-use existing relational database tables — these tables will frequently not be optimally designed for OLAP use.

Multidimensional Expressions ( MDX ) is a query language for OLAP databases, much like SQL is a query language for relational databases.