<![CDATA[Motorcycle sales generate large volumes of transactional data that require systematic management and analysis to support business decision making. This study aims to design and implement a motorcycle sales data warehouse using the Kimball Nine Steps methodology and to perform data analysis and visualization using RapidMiner. The dataset consists of motorcycle sales data including production year, price, model, type, and technical specifications. The results show that the implementation of a star schema successfully integrates data in a structured manner and supports multidimensional analysis. Three-dimensional scatter plot visualizations reveal sales patterns concentrated on mid-aged motorcycles within the medium price range, as well as the dominance of specific models. This study concludes that the integration of data warehousing and data visualization effectively improves information quality and supports data-driven decision making.]]>
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