INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Business Intelligence field [4] provides the solutions for multidimensional analysis using large amount of data from data warehouse. To make the decisions from the raw data available in data warehouse may take huge time. So to make interactive analysis from huge data, multidimensional data cubes can be used. The data cube contains the cells (cuboids) which are aggregation of the data. To access the whole data every time for analysis is too expensive. In this paper we can study different materialization techniques [6] which can compute the data cells at once only. So no need to access whole data, instead one can use these precomputed data cells (cuboids). For efficient data cube computation,[2][5] materialization can starts from base cuboid to apex (target) cuboid in such a way that intermediate cuboids takes less time and space to generate. In materialization we can compute all cuboids or specific cuboids required for analysis purpose.
Keywords:
business intelligence, data warehouse, multidimensional data cubes, cuboids, materialization
Cite Article:
"A Survey on Efficient Data Cube Computation Methodologies for Business Intelligence", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.i351-i354, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305846.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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