Empowering Data Transformation: Transforming Raw Data into A Strategic Planning for E-Commerce Success

Keywords: Business Intellegence, Datawarehouse, ETL, OLAP, Star Schema

Abstract

The ability to transform data is essential to support strategic decision-making in a company or organization. Data transformation can be done by utilizing data warehouse technology. Therefore, it is necessary to know the description of data warehouses that use the Extract, Transform, and Load (ETL) process. This research will focus on implementing Datawarehouse at TechTrove, an e-commerce company using Pentaho Data Integration (PDI). Star Schema organizes data marts and Online Analytical Processing (OLAP) to optimize data warehouse tasks. Business Intelligence (BI) tools are critical in extracting valuable insights and showcasing the platform's analytical capabilities in customer behavior analysis, product evaluation, sales monitoring, and inventory management. This research transformed raw data into a strategic plan to support decisions in E-Commerce companies.

Downloads

Download data is not yet available.

References

L. W. Santoso, "Data warehouse with big data technology for higher education," Procedia Computer Science, vol. 124, pp. 93-99, 2017.

H. Homayouni, "Testing extract-transform-load process in data warehouse systems," in 2018 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), pp. 158-161, Oct. 2018.

W. S. Fana, R. Permana, and M. A. Islam, "Data Warehouse Design With ETL Method (Extract, Transform, And Load) for Company Information Centre," International Journal of Artificial Intelligence Research, vol. 5, no. 2, pp. 132-137, 2021.

K. Mohammed, "Data warehouse design and implementation based on star schema vs. snowflake schema," Int. J. Acad. Res. Bus. Soc. Sci, vol. 9, 2019.

D. R. SHRIVASTAVA, R. Tiwari, K. Mehta, and S. Bano, "Various Olap Technologies and Their Impact on Decision Making," in Proceedings of the International Conference on Innovative Computing & Communication (ICICC), April 2021.

S. Chaudhuri and U. Dayal, "An overview of data warehousing and OLAP technology," Sigmod Record, vol. 26, no. 1, pp. 65-74, 1997.

G. S. Reddy, R. Srinivasu, M. P. C. Rao, and S. R. Rikkula, "Data Warehousing, Data Mining, OLAP and OLTP Technologies are essential elements to support decision-making process in industries," International Journal on Computer Science and Engineering, vol. 2, no. 9, pp. 2865-2873, 2010.

D. R. SHRIVASTAVA, R. Tiwari, K. Mehta, and S. Bano, "Various Olap Technologies and Their Impact on Decision Making," in Proceedings of the International Conference on Innovative Computing & Communication (ICICC), April 2021. (Note: This is a duplicate of reference [5] and should typically be omitted or merged.)

M. S. Almeida, M. Ishikawa, J. Reinschmidt, and T. Roeber, Getting started with data warehouse and business intelligence, IBM redbooks, 1999.

J. Wiratama and M. A. Bagioyuwono, "Improving the Data Management: ETL Implementation on Data Warehouse at Indonesian Vehicle Insurance Industry," International Journal of Science, Technology & Management, vol. 4, no. 5, pp. 1256-1268, Sep. 2023.

P. Hamm and M. Klesel, "AIS Electronic Library (AISeL)," 2021.

S. F. Wijaya, J. Wiratama, and V. Kuswanto, "An Evaluation of Integrating ERP System to Develop a Strategy Business," in 2023 International Conference on Information Management and Technology (ICIMTech), Malang, Indonesia, pp. 1-6, 2023.

E. Gallinucci, M. Golfarelli, and S. Rizzi, "Schema profiling of document-oriented databases," Information Systems, vol. 75, pp. 13-25, 2018.

K. S. Harishkumar, "Multidimensional data model for air pollution data analysis," in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1684-1689, Sep. 2018.

E. Gallinucci, M. Golfarelli, and S. Rizzi, "Approximate OLAP of document-oriented databases: A variety-aware approach," Information Systems, vol. 85, pp. 114-130, 2019.

Published
2024-03-26
Abstract views: 106 times
Download PDF: 60 times
How to Cite
Yang, A., Wiratama, J., & Wijaya, S. (2024). Empowering Data Transformation: Transforming Raw Data into A Strategic Planning for E-Commerce Success. Journal of Information Systems and Informatics, 6(1), 339-348. https://doi.org/10.51519/journalisi.v6i1.665