tailieunhanh - Data Modeling Techniques for Data Warehousing phần 5

Nó là một phương tiện để kết thúc, không phải là kết thúc chính nó. Cuối cùng là thường là cần thiết để thực hiện phân tích và ra quyết định thông qua việc sử dụngYêu cầu mô hình hóa. Mô hình ban đầu có hiệu lực được tiếp tục phát triển thành các mô hình chi tiết chiều | Product Dimension PRODUCT Product Key N Effective from Date D Effective to Date D Description C4O Model Code C8 Unit Cost N9 2 Suggested Wholesale Price N9 2 Suggested Retail Price N9 2 Eligible for Volume Discount c Figure 33. Dimensional and ER Views of Product-Related Data The reason for this difference is the different role the model plays in the data warehouse. To the user the data must look like the data warehouse model. In the operational world a user does not generally use the model to access the data. The operational model is only used as a tool to capture requirements not to access data. Data warehouse design also has a different focus from operational design. Design in an operational system is concerned with creating a database that will perform well based on a well-defined set of access paths. Data warehouse design is concerned with creating a process that will retrieve and transform operational data into useful and timely warehouse data. This is not to imply that there is no concern for performance in a data warehouse. On the contrary due to the amount of data typically present in a 70 Data Modeling Techniques for Data Warehousing data warehouse performance is an essential consideration. However performance considerations cannot be handled in a data warehouse in the same way they are handled in operational systems. Access paths have already been built into the model due to the nature of dimensional modeling. The unpredictable nature of data warehouse queries limits how much further you can design for performance. After implementation additional tuning may be possible based on monitoring usage patterns. One area where design can impact performance is renormalizing or snowflaking dimensions. This decision should be made based on how the specific query tools you choose will access the dimensions. Some tools enable the user to view the contents of a dimension more efficiently if it is snowflaked while for other tools the opposite is true. As well the .