Skip to main content
SpringerLink
Log in

Design and Implementation of Data Warehouse Solution at Kumpulan Wang Persaraan (KWAP)

  • Conference paper
  • First Online:
Data Science and Emerging Technologies (DaSET 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 165))

Included in the following conference series:

  • 400 Accesses

Abstract

The Retirement Fund (Incorporated), also known as KWAP, is a statutory body that manages the pension scheme for Malaysia’s public employees. KWAP has over 550K members. Before the implementation of online data transfer (ODS) in KWAP, finance and management reporting were extracted from the production table. Because everything (dashboard and reporting) was extracted from the main system, the main system or application was impacted and became slow or crushed, so they decided to implement ODS. The data was gathered by the ODS from the main database. The management requires a live dashboard to access the target files or cases to be processed and then display how many cases the operation team has processed. This dashboard will be used to track all progress. However, the live dashboard is not available. However, the live dashboard is inconvenient for reporting because of many inaccurate data in the ODS module. The data warehouse provides a solid platform for integration of the historical data to facilitate information processing systems to produce the information that can be used to support the analytical purpose. Currently, KWAP implementing the ODS concept to handle pensioners’ personal and data transactions. For that, this research focuses on how to implement a data warehouse by proposing a data warehouse design to handle pensioner data at KWAP by moving all reporting part that uses the ODS to the data mart.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Akhter, S., Rahman, N.: Building a customer inquiry database system. Int. J. Technol. Diffus. (IJTD) 6, 59–76 (2015)

    Article  Google Scholar 

  2. Akhter, S., Rahman, N., Rahman, M.N.: Competitive strategies in the computer industry. Int. J. Technol. Diffus. (IJTD) 5, 73–88 (2014)

    Article  Google Scholar 

  3. AlMabhouh, A., Ahmad, A.: Identifying quality factors within data warehouse. In: Proceedings of the Second International Conference on Computer Research and Development, pp. 65–72. IEEE (2010). https://doi.org/10.1109/ICCRD.2010.18

  4. Ballou, D.P., Tayi, G.K.: Enhancing data quality in data warehouse environments. Commun. ACM 42, 1 (1999)

    Article  Google Scholar 

  5. Brohman, M.K., Parent, M., Pearce, M.R., Wade, M.: The business intelligence value chain: data-driven decision support in a data warehouse environment: an exploratory study. In: Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS), pp. 1–10. IEEE (2000)

    Google Scholar 

  6. Cataldo, M., Herbsleb, J.D.: Coordination breakdowns and their impact on development productivity and software failures. IEEE Trans. Software Eng. 39, 343–360 (2013)

    Article  Google Scholar 

  7. Cooper, B.L., Watson, H.J., Wixom, B.H., Goodhue, D.L.: Data warehousing supports corporate strategy at first American corporation. MIS Q. 24, 547–567 (2000)

    Article  Google Scholar 

  8. DeLone, W.J., McLean, E.R.: Information systems success revisited. In: Proceedings of the 35th Hawaii International Conference on System Sciences (HICSS). IEEE Computer Society Press (2002)

    Google Scholar 

  9. Gefen, D., Wyss, S., Lichtenstein, Y.: Business familiarity as risk mitigation in software development outsourcing contracts. MIS Q. 32, 531–551 (2008)

    Article  Google Scholar 

  10. Golfarelli, M., Rizzi, S.: Data Warehouse Design: Modern Principles and Methodologies. McGraw-Hill Osborne Media, New York (2009)

    Google Scholar 

  11. Idris, N., Ahmad, K.: Managing data source quality for data warehouse in manufacturing services. In: Proceedings of the International Conference on Electrical Engineering and Informatics, 17–19 July 2011, Bandung, Indonesia (2011)

    Google Scholar 

  12. Isik, O., Jones, M.C., Sidorova, A.: Business intelligence success: the roles of BI capabilities and decision environments. Inf. Manage. 50, 13–23 (2013)

    Article  Google Scholar 

  13. Keil, M., Carmel, E.: Customer-developer links in software development. Commun. ACM 38, 33–44 (1995)

    Article  Google Scholar 

  14. Leitheiser, R.L.: Data quality in health care data warehouse environments. In: Proceedings of the 34th Hawaii International Conference on System Sciences (HICSS), pp. 1–10. IEEE (2001)

    Google Scholar 

  15. Lu, Y., Ramamurthy, K.: Understanding the link between information technology capability and organizational agility: an empirical examination. MIS Q. 35, 931–954 (2011)

    Article  Google Scholar 

  16. Mithas, S., Ramasubbu, N., Sambamurthy, V.: How information management capability influences firm performance. MIS Q. 35, 237–256 (2011)

    Article  Google Scholar 

  17. Miyamoto, M.: Application of competitive forces in the business intelligence of Japanese SMEs. Int. J. Manage. Sci. Eng. Manage. (IJMSEM) 10, 273–287 (2015)

    Google Scholar 

  18. Rahman, N.: Measuring performance for data warehouses - a balanced scorecard approach. Int. J. Comput. Inf. Technol. (IJCIT) 4, 1–7 (2013)

    Google Scholar 

  19. Paim, F.R.S., Carvalho, A.E., Castro, J.D.: Towards a methodology for requirements analysis of data warehouse systems. In: Proceedings of the XVI Simpósio Brasileiro de Engenharia de Software (SBES2002), Gramado, Rio Grande do Sul, Brazil (2002)

    Google Scholar 

  20. Wijaya, G.: Perancangan data warehouse nilai mahasiswa dengan kimball nine-step methodology. J. Inform. 4(1) (2017)

    Google Scholar 

  21. Kimball, R., Ross, M.: The Kimball Group Reader: Rentlessly Practical Tools for Data Warehousing and Business Intelligence. Wiley Publishing Inc., Indianapolis (2010)

    Google Scholar 

  22. Elazeem, N.M.A., Labib, N.M., Abdella, A.K.: A proposed data warehouse framework to enhance decisions of distribution system in pharmaceutical sector. Egypt. Comput. Sci. J. 43(2), 43–60 (2019)

    Google Scholar 

  23. Girsang, A.S., Arisandi, G., Elysisa, C., Michelle, Saragih, M.H.: Decision support system using data warehouse for retail system. J. Phys. Conf. Ser. 1367(1), 1–6 (2019)

    Google Scholar 

  24. Peng, X.: Analysis of administrative management and decision-making based on data warehouse. In: Proceedings of the 11th International Conference on Measuring Technology and Mechatronics Automation, Qiqihar, China, pp. 527–530 (2019)

    Google Scholar 

  25. Katkar, V., Gangopadhyay, S.P., Rathod, S., Shetty, A.: Sales forecasting using data warehouse and Naïve Bayesian classifier. In: Proceedings of the International Conference on Pervasive Computing, Pune, India, pp. 1–6 (2015)

    Google Scholar 

  26. AbdAlrazig, H.: Designing a data warehousing model to support forecasting and decision making for sales. Doctoral dissertation. Sudan University of Science and Technology (2018)

    Google Scholar 

  27. Torres-Sanchez, R., Navarro-Hellin, H., Guillamon-Frutos, A., San-Segundo, R., Ruiz-Abellón, M.C., Domingo-Miguel, R.: A decision support system for irrigation management: analysis and implementation of different learning techniques. Water 12(2) (2020)

    Google Scholar 

  28. Baumeister, J., Striffler, A.: Knowledge-driven systems for episodic decision support. Knowl.-Based Syst. 88, 45–56 (2015)

    Article  Google Scholar 

  29. Hosio, S., Karppinen, J., Berkel, N., Oppenlaender, J., Goncalves, J.: Mobile decision support and data provisioning for low back pain. Computer 51(8), 34–43 (2018)

    Article  Google Scholar 

  30. Nayak, L.S.A., Das, K., Hota, S., Sahu, B.J.R., Mishra, D.A.: Implementation of data warehouse: an improved data-driven decision-making approach. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds.) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol. 286, pp. 419-427. Springer, Singapore (2022). https://doi.org/10.1007/978-981-16-9873-6_38

  31. Hofer, I.S., Gabel, E., Pfeffer, M., Mahbouba, M., Mahajan, A.: A systematic approach to creation of a perioperative data warehouse. Anesth. Analg. 122(6), 1880–1884 (2016)

    Article  Google Scholar 

Download references

Acknowledgement

The publication of this paper was supported by UNITAR International University, Malaysia and Jaycorp Berhad industry grant.

Author information

Authors and Affiliations

  1. UNITAR International University, Petaling Jaya, Selangor, Malaysia

    Mohamad Fairul Hussein, Paridah Daud, Normaiza Mohamad & Noor Lees Ismail

  2. Jaycorp Berhad, Kuala Lumpur, Malaysia

    Omar Musa

Authors
  1. Mohamad Fairul Hussein
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Paridah Daud
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Omar Musa
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Normaiza Mohamad
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Noor Lees Ismail
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Paridah Daud .

Editor information

Editors and Affiliations

  1. UNITAR Graduate School, UNITAR International University, Selangor, Malaysia

    Yap Bee Wah

  2. University of Tennessee, Knoxville, TN, USA

    Michael W. Berry

  3. Institute for Big Data Analytics and Artificial Intelligence, Universiti Teknologi MARA (UiTM), Shah Alam, Selangor, Malaysia

    Azlinah Mohamed

  4. School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, UK

    Dhiya Al-Jumeily

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hussein, M.F., Daud, P., Musa, O., Mohamad, N., Ismail, N.L. (2023). Design and Implementation of Data Warehouse Solution at Kumpulan Wang Persaraan (KWAP). In: Wah, Y.B., Berry, M.W., Mohamed, A., Al-Jumeily, D. (eds) Data Science and Emerging Technologies. DaSET 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 165. Springer, Singapore. https://doi.org/10.1007/978-981-99-0741-0_14

Download citation

Publish with us

Policies and ethics

Search

Navigation