Sales Analysis on Garment Industry with Datawarehouse and ETL Implementation on Star Schema - Tan, Dasmond; Wiratama, Jansen; Fernandi Wijaya, Santo (AI Society & STMIK Indonesia, 2024)
In the current industrial era, clothing companies face increasingly complex challenges in maintaining the quality and sales of their products. To overcome these obstacles, companies must have a good vision, mission, and decision-making capabilities supported by efficient data management. Data is becoming a valuable asset in Industry 4.0, pivotal in process management, increased productivity, and competitive advantage. This research explores the implementation of Data Warehouse (data warehouse) and ETL (Extraction, Transformation, and Load) processes on star schema for PT Golden Flower Tbk. A data warehouse is a container for storing company data, supporting decision-making, and providing business insights. Meanwhile, the ETL process ensures that the data entered into the warehouse is clean, structured, and ready for analysis. PTA garment manufacturing and exporter company, USPT Golden Flower Tbk, uses the Pentaho application to carry out the ETL process. Pentaho, a Business Intelligence tool, facilitates easy data processing and analysis. This research also explains the use of dimension tables and fact tables in star schemas, which form the basis for more in-depth data analysis. Through visualization and analysis using star schema, Mondrian, and schema workbench, companies can identify sales patterns in each branch and understand which products are most in demand by consumers. The results of the star schema, moMondrianand schema workbench provide a better understanding of the company's sales performance, enabling more informed decision-making and more effective strategies.