Analysis Of Data Warehouse Design Using Powell Method
Abstract
With the evolution in this digital era, many industrial organizations and companies have begun to move towards digitization to increase the company's business opportunities. Data is something that is very useful in a company's business. If the dataprocessed correctly can provide a variety of information needed by the company to continue to grow. Now Data also becomes digital and data processing have many techniques and can provide us with a decision support for the information generated by the data. The data processing is usually called Data Warehouse. In running a business, business owners must certainly analyze a number of things so that the business continues to run and grow, including one of which is a fabric business in Bali, namely CV Phalani Bali. CV Phalani Bali still needs a centralized system that integrates sales data from online stores and offline stores, therefore a data warehouse is needed that can help manage all these data and make it a new information needed by CV Phalani Bali. With the data warehouse, it can help the owner of CV Phalani Bali in reporting and historical information of the business they run. Helps manage historical data and provides strategic information to support evaluation and take decision analysis at the executive level. So one of the data warehouse design methods is used, is the Powell method. This Powell method focuses on the ETL (Extract, Transform, Load) process to become a data warehouse that is ready to be processed by OLAP (Online Analytical Processing). This Powell method will be assisted by Microsoft SQL Server Business Intelligence as a tool that will design and process the sales data into a data warehouse that will produce the information needed by CV Phalani Bali for analyze and make decisions to bring cv phalani bali even more advanced.
Downloads
References
[2] D. T. Anggraeni, M. Mustikasari and C. Wibawa, "Perancangan Data Mart Pada Perusahaan Manufaktur Alat Perkantoran Baja," Jurnal Teknologi Rekayasa, vol. XXI, no. 1, pp. 11-21, 2016.
[3] I. G. Adnyana, M. Sudarma and W. G. Ariastina, "Middleware ETLwith CDC based on Event Driven Programming," International Journal of Engineering and Emerging Technology, vol. III, no. 2, pp. 1-4, 2018.
[4] U. Fadilah, W. W. Winarno and A. Amborowati, "Perancangan Data Warehouse Untuk Sistem Akademik STMIK Kadiri," Jurnal Ilmiah Sistem Informasi dan Teknik Informatika, vol. IV, no. 2, pp. 217-228, 2016.
[5] Rifzan, "Pengertian Data Warehouse Serta Penjelasannya," Robicomp, 22 March 2019. [Online]. Available: https://www.robicomp.com/pengertian-data-warehouse-serta-penjelasannya.html. [Accessed 18 April 2020].
[6] A. Saputra, Zulfachmi and M. Sudarma, "Designing Data Warehouse for Analysis of Culinary Sales with Multidimensional Modeling –Star SchemaDesign(CaseStudy: XYZ Restaurant)," International Journal of Engineering and Emerging Technology, vol. III, no. 1, pp. 71-74, 2018.
[7] Rianto and C. Hadis, "Perancangan Data Warehouse Pada Rumah Sakit (Studi Kasus: BLUD RSU Kota Banjar)," Jurnal Siliwangi, vol. III, no. 2, pp. 214-221, 2017.
[8] R. Dharayani, K. A. Laksitowening and A. P. Yanuarfiani, "Implementasi ETL (Extract, Transform, Load) Pangkalan Data Perguruan Tinggi dengan Menggunakan State-Space Problem," e-Proceeding of Engineering , vol. II, no. 1, pp. 1159-1165, 2015.
[9] R. Wijaya and B. Pudjoatmodjo, "Penerapan Extraction-Transformation-Loading (ETL) Dalam Data Warehouse (Studi Kasus : Departemen Pertanian)," Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI), vol. V, no. 2, pp. 61-75, 2016.
[10] D. Seprianus, "Analisis Dan Perancangan Data Warehouse Akademik Perguruan Tinggi Bina Sriwijaya Berbasis Pentaho Data Integration Kettle," Universitas Bina Darma Palembang, Palembang, 2013.
[11] M. Silvana, R. Akbar and Derisma, "Pengembangan Model Business Intelligence Manajemen Rumah Sakit untuk Peningkatan Mutu Pelayanan (Studi Kasus : Semen Padang Hospital)," Jurnal Edukasi dan Penelitian Informatika , vol. III, no. 2, pp. 124-133, 2017.
[12] Microsoft, "SQL Business Intelligence," Microsoft, [Online]. Available: https://www.microsoft.com/en-us/sql-server/sql-business-intelligence. [Accessed 25 April 2020].
[13] Putri, "Memahani Star Schema dan Snowflake Schema," 15 October 2015. [Online]. Available: http://si142.ilearning.me/2016/10/15/assignment-5-memahani-star-schema-dan-snowflake-schema-putri/. [Accessed 30 April 2020].
[14] K. A. B. Permana, G. B. Subiksa and M. Sudarma, "Design Data Warehouse For Centralized Medical Record," International Journal of Engineering and Emerging Technology, vol. II, no. 2, pp. 47-51, 2017.
Indexed By
