Systems for decision-making support include central data warehouse. A data warehouse contains data from various heterogeneous sources using sophisticated tools by which is ensured gathering, processing, integrating and storing data. The entire process by which is secured retrieval, migration and data storage is called ETL, and it is the foundation of business intelligence. The process of preparing the data is not visible to the end users but it is essential for the successful development of systems that users will use in everyday business. Data collected on this way in subsequent steps over the tools for analysis, reporting or monitoring will be adapted for needs of the end users. This paper defines the architecture of business intelligence. Each component of the architecture is shown in practice. Emphasis is placed on the challenges encountered in developing of data integration and its maintenance. Each project as it is shown starts from conceptual model over which will be build logical model derived in a relational database based on star schema. With Informatica PC tool is presented data integration. Managing data quality is the next step presented by Informatica DQ tool. The collected data are then further analyzed, and pre-prepared results for complex queries are stored using Microsoft Analysis Services tool. The collected data in final step, over reporting tool Microsoft Reporting Services will be presented to the end users.