Abstract
Libraries are service units with high storage complexity as evidenced by more data being stored for each year. The data that is not integrated makes the complex problem because every year the process that is carried out continues to increase, especially for the circulation of loans. As the number of books increases, the circulation of borrowing increases every year. On the other hand, the library must know exactly what collection of books they have and the transactions it has made. A lot of data is owned by the library cannot be utilized optimally, so that the managerial is unable to make full use of the data. In University scale libraries, this problem increases when the data is not fully integrated. In this study, the implementation of a star schema was carried out to solve problems related to data integration using a nine-step methodology, which includes selection, item selection, process dimensions, fact selection, fact storage, ensuring dimension tables, selecting database duration, changing dimensions, determining priorities, and query models. The results of this study indicate that the star schema can be implemented in the case of libraries, data warehouses and OLAP to support decision making for adding books, and produced 3 dimensions of the 4 grains found.
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