{"title":"Conceptual Multidimensional Model","authors":"Manpreet Singh, Parvinder Singh, Suman","volume":12,"journal":"International Journal of Computer and Information Engineering","pagesStart":3841,"pagesEnd":3847,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/3843","abstract":"The data is available in abundance in any business\r\norganization. It includes the records for finance, maintenance,\r\ninventory, progress reports etc. As the time progresses, the data keep\r\non accumulating and the challenge is to extract the information from\r\nthis data bank. Knowledge discovery from these large and complex\r\ndatabases is the key problem of this era. Data mining and machine\r\nlearning techniques are needed which can scale to the size of the\r\nproblems and can be customized to the application of business. For\r\nthe development of accurate and required information for particular\r\nproblem, business analyst needs to develop multidimensional models\r\nwhich give the reliable information so that they can take right\r\ndecision for particular problem. If the multidimensional model does\r\nnot possess the advance features, the accuracy cannot be expected.\r\nThe present work involves the development of a Multidimensional\r\ndata model incorporating advance features. The criterion of\r\ncomputation is based on the data precision and to include slowly\r\nchange time dimension. The final results are displayed in graphical\r\nform.","references":"[1] P. Adriaans and D. Zantinge \"Data Mining\", Pearson Education, USA,\r\n2002, pp. 1-200.\r\n[2] Alexandros Karakasidis \"ETL queues for active data warehousing\"\r\nSixth International Conference on Extending Database Technology,\r\nUSA, 2005, pp. 153-165.\r\n[3] A. L. P. Chen, J-S. Chiu and F. S. C. Tseng, \"Evaluating Aggregate\r\nOperations over imprecise Data\", IEEE Transactions on Knowledge\r\nand Data Engineering, Vol8, 1996, pp.273-284.\r\n[4] C. Bettini, C. E. Dyreson, W. S. Evans, R. T. Snodgrass, X. S. Wang,\r\n\"A Glossary of Time granularity Concepts\", In Temporal Databases:\r\nResearch and Practice, 1998, pp. 406-413.\r\n[5] C. Li and X. S. Wang, \"A Data Model for Supporting On-Line\r\nAnalytical Processing\" Fifth International Conference on Information\r\nand Knowledge Management, 1996, pp. 81-88.\r\n[6] Chang-Sub Park, young Ho Kim, Yoon-Joon Lee, \"Rewriting OLAP\r\nQueries using Materialized Views and Dimension Hierarchies in Data\r\nwarehouses\" IEEE, 2001, pp. 515-523.\r\n[7] Daniel A. Keim, Hans-Peter Kriegel, \"Visualization technique for\r\nMining Large databases: A Comparison\", IEEE Transaction on\r\nKnowledge and Data Engineering,Vol 8., 1996, pp.923-938.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 12, 2007"}