Editing Online analytical processing (section)

{{Short description|Processing mode}}
{{Multiple issues|{{advert|date=June 2024}}
{{buzzwords|date=June 2024}}}}
{{Use mdy dates|date=October 2023}}
In [[computing]], '''online analytical processing (OLAP)''' ({{IPAc-en|ˈ|oʊ|l|æ|p}}), is an approach to quickly answer [[multi-dimensional analytical]] (MDA) queries.<ref name="Codd1993">{{cite web |title=Exploring Business Intelligence Tools: A Comprehensive Guide |url=https://hyscaler.com/insights/business-intelligence-tools/ |website=HyScaler.com |publisher=Codd & Date, Inc}}{{Dead link|date=April 2020|bot=InternetArchiveBot|fix-attempted=yes}}</ref> The term ''OLAP'' was created as a slight modification of the traditional database term [[online transaction processing]] (OLTP).<ref>{{cite web |year=1997 |title=OLAP Council White Paper |url=http://www.symcorp.com/downloads/OLAP_CouncilWhitePaper.pdf |access-date=2008-03-18 |publisher=OLAP Council}}</ref> OLAP is part of the broader category of [[business intelligence]], which also encompasses [[relational database]]s, report writing and [[data mining]].<ref>{{cite book
  |url=https://books.google.com/books?id=M-UOE1Cp9OEC
  |title=Business Intelligence for Telecommunications
  |publisher=CRC Press
  |author=Deepak Pareek
  |year=2007
  |pages=294 pp
  |isbn=978-0-8493-8792-0
  |access-date=2008-03-18
}}</ref> Typical applications of OLAP include [[Financial reporting|business reporting]] for sales, [[marketing]], management reporting, [[business process management]] (BPM),<ref>{{cite book
  |url=http://www.google.com/products?q=9783639222166
  |title=Business Process Management:A Data Cube To Analyze Business Process Simulation Data For Decision Making
  |publisher=[[VDM Verlag|VDM Verlag Dr. Müller e.K.]]
  |author=Apostolos Benisis
  |year=2010
  |pages=204 pp
  |isbn=978-3-639-22216-6
}}</ref> [[budget]]ing and [[forecasting|forecast]]ing, [[financial reporting]] and similar areas, with new applications emerging, such as [[agriculture]].<ref name=ahsan/>

OLAP tools enable users to analyse multidimensional data interactively from multiple perspectives. OLAP consists of three basic analytical operations: consolidation (roll-up), drill-down, and slicing and dicing.<ref name="OBrien">O'Brien, J. A., & Marakas, G. M. (2009). Management information systems (9th ed.). Boston, MA: McGraw-Hill/Irwin.</ref>{{rp|402-403}} Consolidation involves the aggregation of data that can be accumulated and computed in one or more dimensions. For example, all sales offices are rolled up to the sales department or sales division to anticipate sales trends. By contrast, the drill-down is a technique that allows users to navigate through the details. For instance, users can view the sales by individual products that make up a region's sales. 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. These viewpoints are sometimes called dimensions (such as looking at the same sales by salesperson, or by date, or by customer, or by product, or by region, etc.).

[[Database]]s configured for OLAP use a multidimensional data model, allowing for complex analytical and [[ad hoc]] queries with a rapid execution time.<ref>{{cite web
  |url=http://www.dwreview.com/OLAP/Introduction_OLAP.html
  |title=Introduction to OLAP – Slice, Dice and Drill!
  |publisher=Data Warehousing Review
  |author=Hari Mailvaganam
  |year=2007  |access-date=2008-03-18
}}</ref> They borrow aspects of [[navigational database]]s, [[hierarchical database]]s and relational databases.

OLAP is typically contrasted to [[OLTP]] (online transaction processing), which is generally characterized by much less complex queries, in a larger volume, to process transactions rather than for the purpose of business intelligence or reporting. Whereas OLAP systems are mostly optimized for read, OLTP has to process all kinds of queries (read, insert, update and delete).