An Evaluation of the Challenges of Multilingualism in Data Warehouse Development

Nedim Dedić, Clare Stanier


In this paper we discuss Business Intelligence and define what is meant by support for Multilingualism in a Business Intelligence reporting context. We identify support for Multilingualism as a challenging issue which has implications for data warehouse design and reporting performance. Data warehouses are a core component of most Business Intelligence systems and the star schema is the approach most widely used to develop data warehouses and dimensional Data Marts. We discuss the way in which Multilingualism can be supported in the Star Schema and identify that current approaches have serious limitations which include data redundancy and data manipulation, performance and maintenance issues. We propose a new approach to enable the optimal application of multilingualism in Business Intelligence. The proposed approach was found to produce satisfactory results when used in a proof-of-concept environment. Future work will include testing the approach in an enterprise environment.


  1. Anadiotis, G., 2013. Agile business intelligence: reshaping the landscape. , p.3.
  2. Arefin, M.S., Morimoto, Y. & Yasmin, A., 2011. Multilingual Content Management in Web Environment. In 2011 International Conference on Information Science and Applications. pp. 1-9.
  3. Boakye, E.A., 2012. From Design and Build to Implementation and Validation. In C. McKinney, ed. Implementing Business Intelligence in Your Healthcare Organization. Chicago: HIMSS, pp. 73-86.
  4. Brannon, N., 2010. Business Intelligence and E-Discovery. Intellectual Property & Technology Law Journal, 22(7), pp.1-5.
  5. Cenoz, J., 2013. Defining Multilingualism. Annual Review of Applied Linguistics, 33, pp.3-18.
  6. Chaudhuri, S., Dayal, U. & Narasayya, V., 2011. An overview of business intelligence technology. Communications of the ACM, 55(8), p. 88-98 .
  7. Cios, K.J. et al., 2007. Data Mining: A Knowledge Discovery Approach 1st ed., New York, USA: Springer Science+Business Media, LLC.
  8. Collins, R.W., 2002. Software localization for internet software: Issues and methods. IEEE Software.
  9. Corr, L. & Stagnittno, J., 2014. Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema, Leeds: DecisionOne Press.
  10. Cravero, A. & Sepúlveda, S., 2015. Using GORE in Data Warehouse: A Systematic Mapping Study . Latin America Transactions, IEEE (Revista IEEE America Latina) , 13(5), pp.1654 - 1660.
  11. Croatian Government, 1990. The Constitution of the Republic of Croatia. , p.Article 12.1. .
  12. Dekkers, J., Versendaal, J. & Batenburg, R., 2007. Organising for Business Intelligence: A framework for aligning the use and development of information. In BLED 2007 Proceedings. Bled, pp. 625 - 636.
  13. Dokeroglu, T., Sert, S.A. & Cinar, M.S., 2014. Evolutionary Multiobjective Query Workload Optimization of Cloud Data Warehouses . The Scientific World, 2014(14), pp.1 - 16.
  14. European Comission, 2008. Final Report: Commission of the European Communities High Level Group on Multilingualism, Luxembourg.
  15. Forbes, 2015. The World's Biggest Public Companies. Available at: global2000/list/ (Accessed November 24, 2015).
  16. Gouvernement de la République française, 1958. Constitution of France. , p.Article 2.1. .
  17. Government of Federation of Bosnia and Herzegovina, 1995. Federation Constitution. , p.Article 6.1.
  18. Gracia, J. et al., 2012. Challenges for the multilingual Web of Data. Web Semantics: Science, Services and Agents on the World Wide Web, 11, pp.63-71.
  19. Graefe, G. et al., 2013. Elasticity in cloud databases and their query processing. International Journal of Data Warehousing and Mining, 9(2), p.1.
  20. Hannula, M. & Pirttimäki, V., 2003. Business intelligence empirical study on the top 50 Finnish companies. Journal of American Academy of Business, 2, pp.593-599.
  21. Hau, E. & Aparício, M., 2008. Software Internationalization and Localization in Web Based ERP. In SIGDOC 7808 Proceedings of the 26th annual ACM international conference on Design of communication. New York: ACM , pp. 175 - 180.
  22. Heflin, J. & Pan, Z., 2010. Semantic Integration: The Hawkeye Approach. In Semantic Computing. Haboken, New Jersey, US: IEEE Press; John Wiley & Sons, pp. 199-227.
  23. Hensch, K., 2005. IBM History of Far Eastern Languages in Computing, Part 1: Requirements and Initial Phonetic Product Solutions in the 1960s. IEEE Annals of the History of Computing, 27(1), pp.17-26. Available at: wrapper.htm?arnumber=1401743.
  24. Hillier, M., 2003. The role of cultural context in multilingual website usability. Electronic Commerce Research and Applications, 2(1), pp.2-14. Available at:
  25. Huang, S. & Tilley, S., 2001. ssues of content and structure for a multilingual web site. In Proceedings of the 19th annual international conference on computer documentation. ACM, pp. 103-110.
  26. Huff, A., 2013. Big Data II: Business Intelligence - Fleets Analyze Information from several sources to improve overall performance. Commercial Carrier Journal, (April), p.53.
  27. Imhoff, C., Galemmo, N. & Geiger, J.G., 2003. Mastering Data Warehouse Design: Relational and Dimensional Techniques, Indianapolis: Wiley Publishing, Inc.
  28. Inmon, B.W., 2005. Building the Data Warehouse 4th ed., Indianapolis: John Wiley & Sons.
  29. Inmon, B.W., 1995. Building the Data Warehouse 1st ed., New York: Wiley.
  30. Jensen, C.S., Pedersen, T.B. & Thomsen, C., 2010. Multidimensional Databases and Data Warehousing 1st ed., Morgan & Claypool Publishers.
  31. Jovanovic, V., Subotic, D. & Mrdalj, S., 2014. Data Modeling Styles in Data Warehousing. In 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). Opatija, Croatia: MIPRO, pp. 1458 - 1463.
  32. Kimball, R., 2001. Design Tip #24: Designing Dimensional In A Multinational Data Warehouse. Kimball Group. Available at: 06/ design-tip-24-designing-dimensional-in-a-multina tional-data-warehouse/ Accessed December 1, 2015).
  33. Kimball, R. et al., 2008. The Data Warehouse Lifecycle Toolkit 2nd ed., Indianapolis: John Wiley & Sons.
  34. Kimball, R. & Ross, M., 2011. The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling 2nd ed., John Wiley & Sons.
  35. Kingdom of Spain, 1978. Spanish Constitution. , p. Article 3.1.
  36. Law No. 482, 1999. Norme in materia di tutela delle minoranze linguistiche storiche. Gazzetta Ufficiale, 297 (Article 1.1).
  37. Linstedt, D., Graziano, K. & Hultgren, H., 2010. The Business of Data Vault Modeling 2nd .,
  38. Marchand, M. & Raymond, L., 2008. Researching performance measurement systems: An information systems perspective. International Journal of Operations & Production Management, 28(7), pp.663 - 686.
  39. Obeidat, M. et al., 2015. Business Intelligence Technology, Applications, and Trends. International Management Review, 11(2), pp.47-56.
  40. Olszak, C. & Ziemba, E., 2007. Approach to Building and Implementing Business Intelligence Systems. Interdisciplinary Journal of Information, Knowledge & Management, 2, pp.135-148.
  41. Orlov, V., 2014. Data Warehouse Architecture: Inmon CIF, Kimball Dimensional or Linstedt Data Vault? WMP Blog. Available at: http://blog.westmonroepartners .com/data-warehouse-architecture-inmon-cif-kimballdimensional-or-linstedt-data-vault/ (Accessed February 20, 2015).
  42. Ponniah, P., 2004. Data Warehousing Fundamentals: A Comprehensive Guide for IT Professionals, New Yor: John Wiley & Sons.
  43. Poolet, M.A., 2008. Data Warehousing: Rapidly Changing Monster Dimensions. SQL Server Pro. Available at: http:// housing-rapidly-changing-monster-dimensions (Acces sed November 24, 2015).
  44. Popovic, A., Turk, T. & Jaklic, J., 2010. Conceptual Model of Business Value of Business Intelligence Systems. Management: Journal of Contemporary Management, 15(1), pp.5-29.
  45. Purba, S., 1999. Handbook of Data Management 3rd ed., Boca Raton, FL, US: Auerbach, CRC Press.
  46. Sano, M. Di, 2014. Business Intelligence as a Service?: a new approach to manage business processes in the Cloud. In 2014 IEEE 23rd International WETICE Conference. Parma, pp. 155-160.
  47. SAP AG, 2015. SAP Library - XML: BW - Data Warehousing - Modeling. Available at: http:// 2d67ae10000009b38f889/frameset.htm (Accessed March 2, 2015).
  48. Scrapehero, 2015. How many products does sell in comparison to Available at: [Accessed November 24, 2015].
  49. Sen, A. & Sinha, A.P., 2005. A comparison of data warehousing methodologies. Communications of the ACM, 48(3), pp.79-84.
  50. Smith, P., 2012. Professional Website Performance: Optimizing the Front-End and Back-End, Indianapolis, USA: John Wiley & Sons.
  51. Vázquez, S.R., 2013. Localizing Accessibility of Text Alternatives for Visual Content in Multilingual Websites. In ACM SIGACCESS Accessibility and Computing. ACM, pp. 34-37.
  52. Yrjö-Koskinen, P., 1973. Johto - Tiedontarve - Tiedonhankinta. Miten informaatiopalvelu voi palvel la yrityksen johtoa? Publications of Insinöörijärjestö, No.77 - 73.

Paper Citation

in Harvard Style

Dedić N. and Stanier C. (2016). An Evaluation of the Challenges of Multilingualism in Data Warehouse Development . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-187-8, pages 196-206. DOI: 10.5220/0005858401960206

in Bibtex Style

author={Nedim Dedić and Clare Stanier},
title={An Evaluation of the Challenges of Multilingualism in Data Warehouse Development},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},

in EndNote Style

JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - An Evaluation of the Challenges of Multilingualism in Data Warehouse Development
SN - 978-989-758-187-8
AU - Dedić N.
AU - Stanier C.
PY - 2016
SP - 196
EP - 206
DO - 10.5220/0005858401960206