tailieunhanh - Data Modeling Techniques for Data Warehousing phần 7

Chúng tôi bao gồm một số các kỹ thuật áp dụng phổ biến hơn và chỉ ra những vấn đề khác có thể được giải quyết. Các hoạt động chính là một phần của yêu cầu mô hình được minh họa trong Khi các kỹ thuật mô hình chiều được sử dụng như những người được chỉ định trong | do have to take it into account in our modeling approach. Dimension keys in fact tables should be given names that reflect the roles they play for the fact. A dimension key called Time is therefore not a very good idea. From the examples presented above we should provide names for the various time dimensions such as Order Date Shipment Date and Delivery Date see Figure 58 . Figure 58. Dimension Keys and Their Roles for Facts in Dimensional Models. Getting the Measures Right Measures are elements of prime importance for a dimensional model. During the initial dimensional modeling phase candidate measures are determined based on the end-user queries and their requirements in general. Candidate measures identified in this way may not be the best possible choices. We strongly suggest that each and every candidate measure be submitted to a detailed assessment of its representativity and its usefulness for information analysis purposes. It is generally recommended that the measures within the dimensional model be representative from a generic business perspective. Failing to do so will make models nonintuitive and complicated to handle. Failing to do so also will make the dimensional model unstable and difficult to extend beyond a pure local interest. When investigating the quality of candidate measures you should focus on the following main issues Meaning of each candidate measure Expressed in business terms a clear and precise statement of what the measure actually represents is a vital piece of metadata that must be made available to end users. Granularities of the dimensions of each measure Although granularities of dimensions are usually considered at the level of facts it is important that measures incorporated within a fact are evaluated against the dimension keys of that fact. Such an evaluation may reveal that a given measure may better be incorporated in another fact or that granularities should perhaps be changed. Particular attention should be paid to .