Abstract
On-Line Analytical Processing (OLAP) is an expertise that offers data discovery, including capabilities of complex analytical calculations, infinite report viewing and predictive “what if” scenario (forecast) planning. OLAP finds its applications in various Business Intelligence (BI) applications. OLAP’s life blood is multidimensional data. OLAP differs from traditional databases in a way data is stored and conceptualized. As OLAP tools are intended to perform enquiry, these systems deliver fast answers for queries that aggregate large amount of detail data to find general trends in Data Warehouse (DW). A number of OLAP models are available, that show various contradictory trends in Data Warehouse. This paper summarizes the existing OLAP models utilized for extensive list of applications and further compares these models based on different parameters.
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Kaur, H., Kaur, G. (2019). Comprehensive Survey of OLAP Models. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_40
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DOI: https://doi.org/10.1007/978-981-13-0761-4_40
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