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data warehousing architecture andimplementation phần 7

Kho dữ liệu đội ngũ thực hiện xây dựng hoặc mở rộng giản đồ kho hiện có dựa trên thiết kế giản đồ cuối cùng hợp lý sản xuất trong thời gian lập kế hoạch. Nhóm nghiên cứu cũng xây dựng các hệ thống con kho đảm bảo một dòng chảy ổn định, | Data quality tools can help identify and correct data errors ideally at the source systems. If corrections at the source are not possible data quality tools can also be used on the warehouse load images or on the warehouse data itself. However this practice will introduce inconsistencies between the source systems and the warehouse data the warehouse team may inadvertently create data synchronization problems. It is interesting to note that while dirty data continue to be one of the biggest issues for data warehousing initiatives research indicates that data quality investments consistently receive but a small percentage of total warehouse spending. Examples of data quality tools include the following DataFlux. Data Quality Workbench Pine Cone Systems. Content Tracker Prism. Quality Manager Vality Technology. Integrity Data Reengineering Data Loaders Data loaders load transformed data i.e. load images into the data warehouse. If load images are available on the same RDBMS engine as the warehouse then stored procedures can be used to handle the warehouse loading. If the load images do not yet have warehouse keys then data loaders must generate the appropriate warehouse keys as part of the load process. Database Management Systems A database management system is required to store the cleansed and integrated data for easy retrieval by business users. Two flavors of database management systems are currently popular relational databases and Multidimensional databases. Relational Database Management Systems RDBMS All major relational database vendors have already announced the availability or upcoming availability of data warehousing related features in their products. These features aim to make the respective RDBMSes particularly suitable to very large database VLDB implementations. Examples of such features are bit-mapped indexes and parallel query capabilities. Examples of these products include IBM. DB2 Informix. Informix RDBMS Microsoft. SQL Server Oracle. Oracle .