The current library environment is experiencing rapid data collection, particulary from the daily activity of borrowing and returning books. This vast amount of data could potentially be utilized for analysis, but in practice, library information systems are often used solely for operational purposes. Consequently, opportunities to extract valuable insights from this data are limited. Given the situation, this study attempts to design and implement a data warehouse focused on analyzing book borrowing and returning patterns, utilizing PostgreSQL as the primary platform. The research process involved several stages, starting with data collection, needs analysis, data warehouse model design using the star schema, and implementation into PostgreSQL. Afterward, an ETL (Extraction, Transformation, and Loading) process was performed to able to combine library transaction data into a more structured and ready for analysis. From this data, the system was able to generate various insights, such as patterns of books that were borrowed most, medim, and least.
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