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Encyclopedia > OLAP

On Line Analytical Processing, or OLAP, is an approach to quickly provide answers to analytical queries that are dimensional in nature. OLAP is part of the broader category business intelligence, which also includes Extract transform load (ETL), relational reporting and data mining. The typical applications of OLAP are in business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, financial reporting and similar areas. The term OLAP was created as a slight modification of the traditional database term OLTP (On Line Transaction Processing). This article or section does not adequately cite its references or sources. ... Extract, transform, and load (ETL) is a process in data warehousing that involves extracting data from outside sources, transforming it to fit business needs, and ultimately loading it into the data warehouse. ... Data mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns using tools such as classification, association rule mining, clustering, etc. ... Wikibooks has more about this subject: Marketing Look up marketing in Wiktionary, the free dictionary. ... The term Business Process Management (or BPM) refers to activities performed by businesses to improve their processes. ... Budget generally refers to a list of all planned expenses and revenues. ... OLTP (Online Transaction Processing) is a form of transaction processing conducted via computer network. ...


Databases configured for OLAP employ a multidimensional data model, allowing for complex analytical and ad-hoc queries with a rapid execution time. Nigel Pendse has suggested that an alternative and perhaps more descriptive term to describe the concept of OLAP is Fast Analysis of Shared Multidimensional Information (FASMI). They borrow aspects of navigational databases and hierarchical databases that are speedier than their relational kin. The term or expression database originated within the computer industry. ... It has been suggested that this article or section be merged with Dimensional database. ... Nigel Pendse is OLAP analyst and the lead person responsible of The OLAP Report and The OLAP Survey, and is an advisor and speaker on a variety of OLAP related subjects. ... FASMI stands for Fast Analysis of Shared Multidimensional Information. ... Navigational databases incorporate both the network model and hierarchical model of database interfaces. ... A hierarchical database is a kind of database management system that links records together in a tree data structure such that each record type has only one owner, e. ... A relational database is a database that conforms to the relational model, and refers to a databases data and schema (the databases structure of how that data is arranged). ...


The output of an OLAP query is typically displayed in a matrix (or pivot) format. The dimensions form the row and column of the matrix; the measures, the values.

Contents

Functionality

In the core of any OLAP system is a concept of an OLAP cube (also called multidimensional cube). It consists of numeric facts called measures which are categorized by dimensions. The cube metadata is typically created from a star schema or snowflake schema of tables in a relational database. Measures are derived from the records in the fact table and dimensions are derived from the dimension tables. In MOLAP products the cube is populated by copying snapshot of the data from the data source, ROLAP products work directly against the data source without copying data and HOLAP products combine the previous two approaches. OLAP (on-line analytical processing) was a term coined by E.F. Codd & Associates published a white paper in 1994, commissioned by Arbor Software (now Hyperion Solutions), entitled ‘Providing OLAP (On-line Analytical Processing) to User-Analysts: An IT Mandate’. (see also article on OLAP). ... In a data warehouse, a dimension is a data element that categorizes each item in a data set into non-overlapping regions. ... The star schema (sometimes referenced as star join schema) is the simplest data warehouse schema, consisting of a single fact table with a compound primary key, with one segment for each dimension and with additional columns of additive, numeric facts. ... The snowflake schema is a more complex data warehouse model than a star schema, and is a type of star schema. ... A relational database is a database that conforms to the relational model, and refers to a databases data and schema (the databases structure of how that data is arranged). ... A fact table is a data warehousing concept. ... A dimension table is a data warehousing concept. ... MOLAP stands for Multidimensional Online Analytical Processing. ... ROLAP stands for Relational Online Analytical Processing. ... HOLAP (Hybrid Online Analytical Process) is a combination of ROLAP and MOLAP which are other possible implementation of OLAP. HOLAP allows to store part of the data in the MOLAP store and another part of the data in ROLAP store. ...


Aggregations

It has been claimed that for complex queries OLAP cubes can produce an answer in around 0.1% of the time for the same query on OLTP relational data. The single most important mechanism in OLAP which allows to achieve such performance is use of aggregations. Aggregations are built from the fact table by changing the granularity on specific dimensions and aggregating up data along these dimensions. The number of possible aggregations is determined by every possible combination of dimension granularities.


The combination of all possible aggregations and the base data contain the answers to every query which can be answered from the data (as in Gray, Bosworth, Layman, and Pirahesh, 1997). Due to the potentially large number of aggregations to be calculated, often only a predetermined number are fully calculated while the remainder are solved on demand. The problem of deciding which aggregations (a.k.a. views) to calculate is known as the view selection problem. View selection can be constrained by the total size of the selected set of aggregations, the time to update them from changes in the base data, or both. The objective of view selection is typically to minimize the average time to answer OLAP queries, although some studies also minimize the update time as well. Many different approaches have been taken to view selection (which is NP-Complete), including greedy algorithms, randomized search, genetic algorithms and A* search algorithms. In complexity theory, the NP-complete problems are the most difficult problems in NP, in the sense that they are the ones most likely not to be in P. The reason is that if you could find a way to solve an NP-complete problem quickly, then you could use... The greedy algorithm determines the minimum number of US coins to give while making change. ... A genetic algorithm (or short GA) is a search technique used in computing to find true or approximate solutions to optimization and search problems. ... In computer science, A* (pronounced A star) is a graph search algorithm that finds a path from a given initial node to a given goal node (or one passing a given goal test). ...


Types

OLAP systems have been traditionally categorized using the following taxonomy


Multidimensional

Main article: MOLAP

MOLAP is the 'classic' form of OLAP and is sometimes referred to as just OLAP. MOLAP uses database structures that are generally optimal for attributes such as time period, location, product or account code. The way that each dimension will be aggregated is defined in advance by one or more hierarchies. MOLAP stands for Multidimensional Online Analytical Processing. ...


Relational

Main article: ROLAP

ROLAP works directly with relational databases. The base data and the dimension tables are stored as relational tables and new tables are created to hold the aggregated information. Depends on a specialized schema design. ROLAP stands for Relational Online Analytical Processing. ...


Hybrid

Main article: HOLAP

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. For example, for some vendors, a HOLAP database will use relational tables to hold the larger quantities of detailed data, and use specialized storage for at least some aspects of the smaller quantities of more-aggregate or less-detailed data. HOLAP (Hybrid Online Analytical Process) is a combination of ROLAP and MOLAP which are other possible implementation of OLAP. HOLAP allows to store part of the data in the MOLAP store and another part of the data in ROLAP store. ...


Comparison

Each type has certain benefits, although there is disagreement about the specifics of the benefits between providers.


Some MOLAP implementations are prone to database explosion. Database explosion is a phenomenon causing vast amounts of storage space to be used by MOLAP databases when certain common conditions are met: high number of dimensions, pre-calculated results and sparse multidimensional data. The typical mitigation technique for database explosion is not to materialize all the possible aggregation, but only the optimal subset of aggregations based on the desired performance vs. storage trade off.


MOLAP generally delivers better performance due to specialized indexing and storage optimizations. MOLAP also needs less storage space compared to ROLAP because the specialized storage typically includes compression techniques. In computer science and information theory, data compression or source coding is the process of encoding information using fewer bits (or other information-bearing units) than an unencoded representation would use through use of specific encoding schemes. ...


ROLAP is generally more scalable. However, large volume pre-processing is difficult to implement efficiently so it is frequently skipped. ROLAP query performance can therefore suffer.


Since ROLAP relies more on the database to perform calculations, it has more limitations in the specialized functions it can use.


HOLAP encompasses a range of solutions that attempt to mix the best of ROLAP and MOLAP. It can generally pre-process quickly, scale well, and offer good function support.


Other types

The following acronyms are also used sometimes, although they are not as widespread as the ones above

  • WOLAP - Web-based OLAP
  • DOLAP - Desktop OLAP
  • RTOLAP - Real-Time OLAP

// RTOLAP - Real Time OLAP Whilst many OLAP Servers such as Microsoft Analysis Services store pre-calculating consolidations and calculated elements to achieve rapid response times a Real Time OLAP Server will calculate the values on the fly, when they are required. ...

APIs and query languages

Unlike relational databases - which had SQL as the standard query language, and wide-spread 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 (ODBO) specification from Microsoft which appeared in 1997 and introduced the MDX query language. Several OLAP vendors - both server and client - adopted it. In 2001 Microsoft and Hyperion announced the XML for Analysis specification, which was endorsed by most of the OLAP vendors. Since this also used MDX as a query language, MDX became the de-facto standard in the OLAP world. A relational database is a database based on the relational model. ... OLE DB for OLAP (abbreviated ODBO) is a Microsoft published specification and an industry standard for multi-dimensional data processing. ... Microsoft is one of few companies engaging itself in the console wars Where they are up against sony, nintendo, and of course sharps new console which may cause a threat. ... Multidimensional Expressions (MDX) is a query language for OLAP databases, much like SQL is a query language for relational databases. ... Microsoft is one of few companies engaging itself in the console wars Where they are up against sony, nintendo, and of course sharps new console which may cause a threat. ... Hyperion Solutions Corporation is a business performance management software company, located in Santa Clara, California, USA. Many of its products are targeted at the Business Intelligence market. ... XML for Analysis (abbreviated as XMLA) is the industry standard for data access in analytical systems, such as OLAP and Data Mining. ... Multidimensional Expressions (MDX) is a query language for OLAP databases, much like SQL is a query language for relational databases. ... Multidimensional Expressions (MDX) is a query language for OLAP databases, much like SQL is a query language for relational databases. ...


Products

History

The first product which performed OLAP queries was IRI's (Information Resources Incorporated )Express which was released in 1970 (and acquired by Oracle in 1995). However, the term did not appear until 1993 when it was coined by Ted Codd, who has been described as "the father of the relational database". Codd's paper resulted from a short consulting assignment which Codd undertook for former Arbor Software (now Hyperion Solutions), as a sort of marketing coup: the company had released its own OLAP product — Essbase — a year earlier. As a result Codd's "twelve laws of online analytical processing" were explicit in their reference to Essbase. There was some ensuing controversy and when Computerworld learned that Codd was paid by Arbor, it retracted the article. OLAP market experienced strong growth in late 90s with dozens of commercial products going into market. In 1998, Microsoft released its first OLAP Server - Microsoft Analysis Services, which drove wide adoption of OLAP technology and moved it into mainstream. In the mid 2000, the Open Source OLAP market began to establish itself, with several companies springing up with offerings. 1970 (MCMLXX) was a common year starting on Thursday (the link is to a full 1970 calendar). ... Oracle Corporation (NASDAQ: ORCL) is one of the major companies developing database management systems (DBMS), tools for database development, middle-tier software (Fusion Middleware), enterprise resource planning software (ERP), customer relationship management software (CRM) and supply chain planning (SCM) software. ... 1993 (MCMXCIII) was a common year starting on Friday of the Gregorian calendar and marked the Beginning of the International Decade to Combat Racism and Racial Discrimination (1993-2003). ... Edgar F. Ted Codd (August 23, 1923 - April 18, 2003) was a British computer scientist who made seminal contributions to the theory of relational databases. ... Hyperion Solutions Corporation is a business performance management software company, located in Santa Clara, California, USA. Many of its products are targeted at the Business Intelligence and Business performance management market. ... Essbase is a multidimensional database management system (MDBMS) that provides a multidimensional database platform upon which to build analytic applications, ie. ... 1998 (MCMXCVIII) was a common year starting on Thursday of the Gregorian calendar, and was designated the International Year of the Ocean. ... Microsoft is one of few companies engaging itself in the console wars Where they are up against sony, nintendo, and of course sharps new console which may cause a threat. ... Microsoft Analysis Services is a group of OLAP and Data Mining services provided in Microsoft SQL Server. ... This article is about the year 2000. ...


Market shares

According to the influential OLAP Report site, the market shares for the top commercial OLAP products in 2006 were:

  1. Microsoft Corporation - 31.6%
  2. Hyperion Solutions Corporation - 18.9%
  3. Cognos - 12.9%
  4. Business Objects - 7.3%
  5. MicroStrategy - 7.3%
  6. SAP AG - 5.8%
  7. Cartesis SA - 3.7%
  8. Applix - 3.6%
  9. Infor - 3.5%
  10. Oracle Corporation - 3.4%

Microsoft Corporation (NASDAQ: MSFT), (founded 1975), headquartered in Redmond, Washington, USA, is the worlds largest software company (with over 50,000 employees in various countries, as of May 2004). ... Hyperion Solutions Corporation is a business performance management software company, located in Santa Clara, California, USA. Many of its products are targeted at the Business Intelligence market. ... Cognos (TSX: CSN, NASDAQ: COGN) is an Ottawa, Ontario based company which makes business intelligence (BI) and performance planning software. ... Business Objects is the worlds leading business intelligence (BI) software company[citation needed] with more than 39,000 customers worldwide. ... MicroStrategy is a business analysis software tool. ... SAP AG (ISIN: DE0007164600, FWB: SAP, NYSE: SAP) is the largest European software enterprise, with headquarters in Walldorf, Germany. ... Applix Inc. ... Oracle Corporation (NASDAQ: ORCL) is one of the major companies developing database management systems (DBMS), tools for database development, middle-tier software (Fusion Middleware), enterprise resource planning software (ERP), customer relationship management software (CRM) and supply chain planning (SCM) software. ...

See also

This article or section does not adequately cite its references or sources. ... A data warehouse is a record of an enterprises past transactional and operational activities, stored in a database. ... Data mining (DM), also called Knowledge-Discovery in Databases (KDD) or Knowledge-Discovery and Data Mining, is the process of automatically searching large volumes of data for patterns using tools such as classification, association rule mining, clustering, etc. ... Predictive analytics encompasses a variety of techniques from statistics and data mining that process current and historical data in order to make “predictions” about future events. ...

External links


  Results from FactBites:
 
OLAP from Cognos Software (337 words)
OLAP technology presents this complex data in ways that are simple to understand and manipulate, and gives enterprises the ability to react more quickly than competitors to new intelligence.
Twenty-five years of expertise in information management makes Cognos an ideal provider of OLAP tools to enterprises in both the private and public sectors.
Top enterprises in every industry employ Cognos solutions and OLAP applications to maintain their competitive edge and give employees fast access to critical information that can aid and improve performance.
SAS | Business Intelligence | OLAP (305 words)
OLAP cubes can be stored on any major hardware platform, from Microsoft Server 2003, HP/UX, AIX and Solaris, up to z/OS on mainframes.
OLAP data storage and navigation are integrated into the SAS BI reporting environment.
Full-featured interactive OLAP client applications allow users to take advantage of OLAP functions as needed to match their needs and skills.
  More results at FactBites »

 
 

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