An information system called a data warehouse contains historical and exchangeable data from one or more sources (Yang et al., 2019). The data warehouse concept simplifies the organizational reporting and analysis process. As an information system containing historical and exchanged data from various sources, data warehouse architecture is complex. There are three approaches to creating data warehouse tiers: single-tier, two-tier, and three-tier (Smith, 2022). To make the entire ecosystem functional, manageable, and accessible, the data warehouse is built on an RDBMS server as the main information repository, surrounded by several fundamental data warehouse components. As the main database and framework of the data warehouse environment, the data warehouse database is one of the key elements of the data warehouse design. The database uses RDBMS technology in its implementation. However, this type of implementation is limited by the fact that standard RDBMS systems are designed to handle transactional databases rather than store data. The second part is tools for procurement, acquisition, cleansing and transformation (ETL) (Yang et al., 2019). The transformations, aggregations, and other customizations required to transform the data into a single format in the data warehouse are performed using data source, transformation, and migration tools. ETL (Extract, Transform and Load) tool is another name for it. continue…