Abstract
Facing with growing data volumes and deeper analysis requirements, current development of Business Intelligence (BI) and Data warehousing systems (DWHs) is a challenging and complicated task, which largely involves in ad-hoc integration and data re-engineering. This arises an increasing requirement for a scalable application framework which can be used for the implementation and administration of diverse BI applications in a straight forward and cost-efficient way. In this context, this paper presents a large-scale application framework for standardized BI applications, supporting the ability to define and construct data warehouse processes, new data analytics capabilities as well as to support the deployment requirements of multi scalable front-end applications. The core of the framework consists of defined metadata repositories with pre-built and function specific information templates as well as application definition. Moreover, the application framework is also based on workflow mechanisms for developing and running automatic data processing tasks. Hence, the framework is capable of offering an unified reference architecture to end users, which spans various aspects of development lifecycle and can be adapted or extended to better meet application-specific BI engineering process.
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Chuck, H., Jeff, W., Karen, C.: Navigating the Next-Generation Application Architecture. IT Professional 11(2), 18–22 (2009)
David, P., Awais, R., Alexandru, T., Andreas, S.: An architectural pattern for designing component-based application frameworks. Software: Practice and Experience 36(2), 157–190 (2006)
Giuseppe, D., Deniz, H., Madan, J., Gunavardhan, K., Avinash, L., Alex, P., Swaminathan, S., Peter, V., Werner, V.: Dynamo: amazon’s highly available key-value store. In: Proceedings of Twenty-First ACM SIGOPS Symposium on Operating Systems Principles, SOSP 2007, pp. 205–220. ACM, New York (2007)
Goeken, M., Knackstedt, R.: Multidimensional Reference Models for Data Warehouse Development. In: Proceedings of the International Conference on Enterprise Information Systems, ICEIS, pp. 347–354 (2007)
Kimball, R., Ross, M., Thornthwaite, W., Mundy, J., Becker, B.: The Data Warehouse Lifecycle Toolkit. Wiley Publishing (2008)
Knackstedt, R., Klose, K.: Configurative reference model-based development of data warehouse systems. In: Khosrow-Pour, M. (ed.) Proceedings of the 16th Information Resources Management Association International Conference, RMA 2005, pp. 32–39 (2005)
Luján-Mora, S., Trujillo, J.: Comprehensive Method for Data Warehouse Design. In: Proceedings of the 5th International Workshop on Design and Management of Data Warehouses, DMDW 2003, pp. 1.1–1.14 (2003)
Mohamed, F., Douglas, C.S.: Object-oriented application frameworks. Commun. ACM 40(10), 32–38 (1997)
Oracle. Enabling Pervasive BI Through a Practical Data Warehouse Reference Architecture (2010)
Oscar, R., Alberto, A.: Automating multidimensional design from ontologies. In: Proceedings of the the ACM Tenth International Workshop on Data Warehousing and OLAP, Lisbon, Portugal, pp. 1–8. ACM (2007)
Oscar, R., Diego, C., Alberto, A., Mariano, R.M.: Discovering functional dependencies for multidimensional design. In: Proceedings of the The ACM Twelfth International Workshop on Data Warehousing and OLAP, Hong Kong, China, pp. 1–8. ACM (2009)
Spahn, M., Kleb, J., Grimm, S., Scheidl, S.: Supporting business intelligence by providing ontology-based end-user information self-service. In: Proceedings of the the First International Workshop on Ontology-Supported Business Intelligence, pp. 1–12. ACM (2008)
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Anh Hoang, D.T., Tran, H., Nguyen, B.T., Tjoa, A.M. (2012). Towards the Development of Large-Scale Data Warehouse Application Frameworks. In: Møller, C., Chaudhry, S. (eds) Re-conceptualizing Enterprise Information Systems. Lecture Notes in Business Information Processing, vol 105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28827-2_7
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DOI: https://doi.org/10.1007/978-3-642-28827-2_7
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