{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,6]],"date-time":"2024-06-06T10:36:14Z","timestamp":1717670174764},"reference-count":28,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,1]]},"abstract":"In the Big Data warehouse context, a column-oriented NoSQL database system is considered as the storage model which is highly adapted to data warehouses and online analysis. Indeed, the use of NoSQL models allows data scalability easily and the columnar store is suitable for storing and managing massive data, especially for decisional queries. However, the column-oriented NoSQL DBMS do not offer online analysis operators (OLAP). To build OLAP cubes corresponding to the analysis contexts, the most common way is to integrate other software such as HIVE or Kylin which has a CUBE operator to build data cubes. By using that, the cube is built according to the row-oriented approach and does not allow to fully obtain the benefits of a column-oriented approach. In this article, the focus is to define a cube operator called MC-CUBE (MapReduce Columnar CUBE), which allows building columnar NoSQL cubes according to the columnar approach by taking into account the non-relational and distributed aspects when data warehouses are stored.<\/jats:p>","DOI":"10.4018\/ijdsst.2020010101","type":"journal-article","created":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T17:37:36Z","timestamp":1571679456000},"page":"1-24","source":"Crossref","is-referenced-by-count":13,"title":["Big Data Warehouse"],"prefix":"10.4018","volume":"12","author":[{"given":"Khaled","family":"Dehdouh","sequence":"first","affiliation":[{"name":"Computer Engineering Department of Cherchell Military Academy, TIPAZA Algeria"}]},{"given":"Omar","family":"Boussaid","sequence":"additional","affiliation":[{"name":"ERIC Laboratory\/ University of Lyon 2, Bron, France"}]},{"given":"Fadila","family":"Bentayeb","sequence":"additional","affiliation":[{"name":"ERIC Laboratory\/ University of Lyon, Lyon 2, Bron, France"}]}],"member":"2432","reference":[{"key":"IJDSST.2020010101-0","doi-asserted-by":"publisher","DOI":"10.1145\/1376616.1376712"},{"key":"IJDSST.2020010101-1","doi-asserted-by":"crossref","unstructured":"Abello, A., Ferrarons, F., & Romero, O. (2011). Building cubes with MapReduce. 14th international workshop on Data Warehousing and OLAP. (pp. 17-24). Glasgow, Scotland, UK.","DOI":"10.1145\/2064676.2064680"},{"issue":"1","key":"IJDSST.2020010101-2","first-page":"9","article-title":"Business analytics in (a) blink.","volume":"35","author":"R.Barber","year":"2012","journal-title":"A Quarterly Bulletin of the Computer Society of the IEEE Technical Committee on Data Engineering"},{"key":"IJDSST.2020010101-3","doi-asserted-by":"publisher","DOI":"10.1145\/304182.304214"},{"key":"IJDSST.2020010101-4","doi-asserted-by":"crossref","unstructured":"Bhogal, J., & Choksi, I. (2015). Handling big data using NoSQL. In Proceedings of the 29th International Conference on Advanced Information Networking and Applications Workshops (pp. 393-398). 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Academic Press."},{"issue":"4","key":"IJDSST.2020010101-13","first-page":"45","article-title":"SAP HANA database: Data management for modern business applications","volume":"40","author":"F.Farber","year":"2012","journal-title":"Special Interest Group on Management of Data Record Journal"},{"key":"IJDSST.2020010101-14","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijinfomgt.2014.10.007"},{"key":"IJDSST.2020010101-15","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009726021843"},{"issue":"1","key":"IJDSST.2020010101-16","first-page":"40","article-title":"Monetdb: Two decades of research in column-oriented database architectures","volume":"35","author":"S.Idreos","year":"2012","journal-title":"A Quarterly Bulletin of the Computer Society of the IEEE Technical Committee on Data Engineering"},{"key":"IJDSST.2020010101-17","author":"C.Imho","year":"2003","journal-title":"Relational Modeling and Data Warehouse Design"},{"key":"IJDSST.2020010101-18","author":"W.Inmon","year":"1992","journal-title":"Building the data warehouse"},{"issue":"1","key":"IJDSST.2020010101-19","first-page":"25","article-title":"Business intelligence and NoSQL databases.","volume":"1","author":"D.Jerzy","year":"2012","journal-title":"Information Systems Management"},{"issue":"12","key":"IJDSST.2020010101-20","first-page":"1790","article-title":"The vertica analytic database: C-store 7 years later","volume":"5","author":"A.Lamb","year":"2012","journal-title":"Proceedings of the Very Large Database Endowment"},{"key":"IJDSST.2020010101-21","first-page":"15","article-title":"Columnar storage in SQL server.","volume":"35","author":"A.Larson","year":"2012","journal-title":"A Quarterly Bulletin of the Computer Society of the IEEE Technical Committee on Data Engineering"},{"key":"IJDSST.2020010101-22","doi-asserted-by":"crossref","unstructured":"Lezak, D., & Eastwood, V. (2009). Data warehouse technology by infobright. In Proceedings of the Special Interest Group on Management of Data international conference (pp. 841-846). Academic Press.","DOI":"10.1145\/1559845.1559933"},{"key":"IJDSST.2020010101-23","doi-asserted-by":"crossref","unstructured":"Lezak, D., Wrblewski, J., Eastwood, V., & Synak, P. (2008). Brighthouse: an analytic data warehouse for adhoc queries. In Proceedings of the Very Large Database Endowment (pp.1337-1345).","DOI":"10.14778\/1454159.1454174"},{"key":"IJDSST.2020010101-24","unstructured":"O\u2019Neil, P., O\u2019Neil, B., & Chen, X. (2007). The star schema benchmark (SSB). Retrieved from http:\/\/www.cs.umb.edu\/~poneil\/StarSchemaB.PDF"},{"key":"IJDSST.2020010101-25","unstructured":"Rabuzin, K., & Modruan, N. (2014). Business intelligence and column-oriented databases. In Proceedings of the Central European Conference on Information and Intelligent Systems (pp. 12-16). 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