Development of the Design Methodology for Large-scale Data Warehouse based on MongoDB
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A data warehouse is a system that collectively manages and integrates data of a company. And provides the basis for decision making for management strategy. Nowadays, analysis data volumes are reaching critical size challenging traditional data ware housing approaches. Current implemented solutions are mainly based on relational database that are no longer adapted to these data volume. NoSQL solutions allow us to consider new approaches for data warehousing, especially from the multidimensional data management point of view. In this paper, we extend the data warehouse design methodology based on relational database using star schema, and have developed a consistent design methodology from information requirement analysis to data warehouse construction for large scale data warehouse construction based on MongoDB, one of NoSQL.
Abstract
A data warehouse is a system that collectively manages and integrates data of a company. And provides the basis for decision making for management strategy. Nowadays, analysis data volumes are reaching critical size challenging traditional data ware housing approaches. Current implemented solutions are mainly based on relational database that are no longer adapted to these data volume. NoSQL solutions allow us to consider new approaches for data warehousing, especially from the multidimensional data management point of view. In this paper, we extend the data warehouse design methodology based on relational database using star schema, and have developed a consistent design methodology from information requirement analysis to data warehouse construction for large scale data warehouse construction based on MongoDB, one of NoSQL.
참고문헌 (12)
- Jacobs, A., "The pathologies of big data", Communications of the ACM, 52(8), pp.36~44 (2009)
- Stonebraker, M., "New Opportunities for New SQL", Communications of the ACM, 55(11), pp.10~11 (2012)
- Cuzzocrea, Alfredo, "Data warehousing and OLAP over big data: current challenges and future research directions", Proceedings of the sixteenth international workshop on Data warehousing and OLAP (2013)
- Dehdouh, Khaled, "Columnar nosql star schema benchmark", International Conference on Model and Data Engineering (2014)
- Chevalier M, "Implementing Multidimensional Data Warehouses into NoSQL", 17th International Conference on Enterprise Information Systems, 1, pp.172~183 (2015)
- W.H.Inmon, "Building the Data Warehouse" (2002), John Wiley & Sons
- Pereira, Daniel, "Data warehouses in MongoDB vs SQL Server: A comparative analysis of the querie performance", Information Systems and Technologies (CISTI), 2015 10th Iberian Conference on. IEEE (2015)
- Bicevska, Zane, "Towards NoSQL-based Data Warehouse Solutions", Procedia Computer Science, 104, pp.104~111 (2017)[DOI]
- Michael Dirolf, "MongoDB The Definitive Guide" (2013), O'ReillyMedia
- Christopher Adamson, "Star Schema The Complete Reference" (2010), McGraw-Hill Osborne
- Mamenko, J., "Introduction to data modeling and msaccess", Lecture Notes on Information Resources (2004)
- Hoberman, S., "DataModeling for MongoDB" (2014), Technics Publications