Data warehousing has become an important strategy to integrate heterogeneous information sources in organizations. However, the data quality problems are happened when loading and continuously refreshing huge amounts of data from a variety of sources. Moreover, data warehouses are used for decision making, so that the correctness of their data is vital to avoid wrong decisions. Therefore, in this paper, we classify data quality problems during the so-called ETL process (extraction, transformation & loading). We also propose a data quality assurance mechanism to solve the data quality problems in data warehouses.