Albany, NY -- (SBWIRE) -- 12/10/2018 -- Online analytical processing (OLAP) is a technology for multidimensional analysis of business data. OLAP tools perform complex calculations, data discovery, trend analysis, and data modeling. It is the foundation for business applications such as analysis, planning, financial reporting, simulation models, business performance management, budgeting, forecasting, and knowledge discovery. OLAP enables ad hoc analysis of data in multiple dimensions, thereby providing insight for making better business decisions. OLAP systems are categorized into relational OLAP (ROLAP), multidimensional OLAP (MOLAP), and hybrid OLAP (HOLAP). OLAP software combines the benefits of relational tables and multidimensional business data modeling in real-time. It maintains a constant connection with back-end systems and delivers real-time reports/analytics in excel and other tools such as dashboards and query tools.

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Presently, commoditization and consolidation of multiple technologies is a major trend in the market. Hence, the need for OLAP and business intelligence is rising along with customer relationship management (CRM) and enterprise performance measurement (EPM) solutions. OLAP is mostly integrated within Business Intelligence (BI) platforms, while online analytical processing, reporting, querying, dashboards, data visualization, and data exploration are considered as separate categories within BI. The demand for BI platforms from enterprise software providers, such as Microsoft Corporation, SAP SE, and Oracle Corporation, is more rather than independent OLAP tools. Most independent BI vendors are likely to be absorbed into industry-specific enterprise software solutions during the forecast period. Hence, the demand for standalone OLAP tools is expected to reduce. OLAP takes a long time to perform business analysis. Hence, in-memory OLAP is the latest technology trend in online analytical processing market. In-memory OLAP technology helps improve overall performance and analysis and as it operates within the memory, the time required for analysis is reduced significantly. The online analytical processing market is dominated by a few established players. These players acquire small players entering the online analytical processing market. In-memory OLAP is projected to create opportunities for small players and during the forecast period. Leading players, such as IBM Corporation, have offer in-memory online analytical processing platforms. IBM Cognos has introduced TM1, an in-memory OLAP 64-bit architecture platform.

The global online analytical processing market can be segmented based on type, solution type, organization size, end-use industry, and region. In terms of type, the online analytical processing market can be classified into ROLAP, MOLAP, HOLAP, and others. The MOLAP segment accounts for a dominant share of the online analytical processing market. Based on solution type, the market can be bifurcated into integrated and standalone. The integrated segment is anticipated to continue to dominate the online analytical processing market between 2018 and 2026. In terms of organization size, the online analytical processing market can be segregated into small & medium enterprises (SMEs) and large enterprises. Based on end-use industry, the online analytical processing market can be categorized into Banking, Financial Services, and Insurance (BFSI), retail, IT & telecom, manufacturing, health care, and others.

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Based on region, the global online analytical processing market can be categorized into North America, Asia Pacific, Middle East & Africa, South America, and Europe. The market in Asia Pacific is fueled by the increase in adoption of OLAP in enterprise software by a large number of SMEs in the region.

Key players operating in the global online analytical processing market include IBM Corporation, Oracle Corporation, MicroStrategy Incorporated, Microsoft Corporation, SAP SE, Jedox AG, Pentaho Corporation (Mondrian), Apache Software Foundation (Apache Kylin), icCube Software llc, Hypercube Consulting PTE LTD, and DataBrewery (Cubes). These players focus on the application needs of buyers and strategically develop products. The market is fragmented and established companies are engaging in mergers and acquisitions to gain additional capabilities and market share.

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