DESIGNING A DATA MART FOR OPTIMIZING CLOTHING SALES AT C STORE

Authors

Ellen Gabriel Limbor Universitas Tarumanagara, Jakarta, Indonesia
Jap Tji Beng Universitas Tarumanagara
Desi Arisandi Universitas Tarumanagara, Jakarta, Indonesia
Sri Tiatri Universitas Tarumanagara, Jakarta, Indonesia
Rahmiyana Nurkholiza Universitas Tarumanagara, Jakarta, Indonesia
Tasya Mulia Salsabila Universitas Indonesia, Indonesia
Vienchenzia Oeyta Dwitama Dinatha INTI International University, Malaysia

DOI:

Abstract

Data plays a crucial role in supporting strategic decision-making, particularly in the retail sector like C Store. To enhance sales performance and understand purchasing trends, an effective system such as a data mart is needed. This study aims to design a data mart that can be used to analyze sales data at C Store to support data-driven decision-making. The methodology used is the nine-step Kimball approach in data mart design. The ETL (Extract, Transform, Load) process is used to manage sales transaction data collected from the period of 2021 to 2024. The result of this study is a data mart with a star schema, consisting of fact and dimension tables, enabling the analysis of sales performance based on product categories and time. The implementation of this data mart is expected to assist C Store in managing data efficiently, supporting strategic decision-making, and improving business operational effectiveness.

Keywords: Data Mart, Kimball's Nine-Step Process, Clothing Sales.

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