Thứ hai, một kho dữ liệu có thể nâng cao năng suất kinh doanh bởi vì nó có thể nhanh chóng và hiệu quả thu thập thông tin chính xác mô tả các tổ chức. Thứ ba, một kho dữ liệu tạo điều kiện quản lý quan hệ khách hàng, bởi vì nó cung cấp một cái nhìn nhất quán của khách hàng và các mặt hàng trên tất cả các ngành nghề kinh doanh, tất cả các phòng ban, và tất cả các thị trường. | 206 Chapter 4 Data Cube Computation and Data Generalization Step 2 collects statistics on the working relation. This requires scanning the relation at most once. The cost for computing the minimum desired level and determining the mapping pairs v v for each attribute is dependent on the number of distinct values for each attribute and is smaller than N the number of tuples in the initial relation. Step 3 derives the prime relation P. This is performed by inserting generalized tuples into P. There are a total of N tuples in w and p tuples in P. For each tuple t in w we substitute its attribute values based on the derived mapping-pairs. This results in a generalized tuple t. If variation a is adopted each t takes O logp to find the location for count increment or tuple insertion. Thus the total time complexity is O N X log p for all of the generalized tuples. If variation b is adopted each t takes O 1 to find the tuple for count increment. Thus the overall time complexity is O N for all of the generalized tuples. Many data analysis tasks need to examine a good number of dimensions or attributes. This may involve dynamically introducing and testing additional attributes rather than just those specified in the mining query. Moreover a user with little knowledge of the truly relevant set of data may simply specify in relevance to in the mining query which includes all of the attributes into the analysis. Therefore an advanced concept description mining process needs to perform attribute relevance analysis on large sets of attributes to select the most relevant ones. Such analysis may employ correlation or entropy measures as described in Chapter 2 on data preprocessing. Presentation of the Derived Generalization Attribute-oriented induction generates one or a set of generalized descriptions. How can these descriptions be visualized The descriptions can be presented to the user in a number of different ways. Generalized descriptions resulting from .
