Abstract:
Data warehousing is an essential element of decision support. It aims at enabling the knowledge user to make better and faster daily business decisions. In order to supply a decisional database, meta-data is needed to enable the communication between various function areas of the warehouse and an ETL tool (Extraction, Transformation, and Load) is needed to define the warehousing process. The developers use a mapping guideline to specify the ETL tool with the mapping expression of each attribute. In this paper, we will define a model covering different types of mapping expressions. We will use this model to create an active ETL tool. In our approach, we use queries to achieve the warehousing process. SQL queries will be used to represent the mapping between the source and the target data. Thus, we allow DBMS to play an expanded role as a data transformation engine as well as a data store. This approach enables a complete interaction between mapping meta-data and the warehousing tool. In addition, this paper investigates the efficiency for a Query-based data warehousing tool. It describes a query generator for reusable and more efficient data warehouse (DW) processing. Besides exposing the advantages of this approach, this paper shows a case study based on real scale commercial data to verify our tool features.
