Enhancing Sales Reporting with Data Warehousing and Visualization: A Case Study at Graha Mas
DOI:
https://doi.org/10.69616/mit.v2i2.237Keywords:
Business Intelligence, Data Warehouse, ETL, Google Data Studio, Sales VisualizationAbstract
This study aims to enhance the sales reporting process by implementing a data warehouse and interactive data visualization, with a case study at Graha Mas. The research adopts the Kimball Nine Step Methodology to guide the development of the data warehouse, supported by the Extract, Transform, Load (ETL) process using Pentaho Data Integration (PDI). Sales data sourced from Excel files undergoes batch processing to ensure data consistency and cleanliness before being stored in the warehouse. A star schema model was applied to structure the data warehouse, consisting of dimension tables for customers, products, and locations, and fact tables for sales categorized by customer, product, and city. The final data is visualized through Google Data Studio dashboards, enabling users to interactively explore sales trends by product, time period, and region. These visualizations assist business decision-makers in identifying high-performing products, monitoring regional sales distribution, and planning inventory more effectively. User acceptance testing (UAT) involving business users resulted in an acceptance score of 89%, indicating that the system meets user needs in terms of data clarity, accuracy, and usability. This research concludes that the proposed solution significantly improves the sales monitoring process at Graha Mas and can serve as a practical reference for similar businesses seeking to adopt cloud-based business intelligence solutions.
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