Tham khảo tài liệu 'microsoft data mining integrated business intelligence for e commerc and knowledge phần 5', công nghệ thông tin, cơ sở dữ liệu phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 116 The data mart Figure Example of the hierarchical nature of a Microsoft data mining analysis case data tables to produce both star schemas for multidimensional viewing as well as relational tables for mining. The way this information is stored assigns a record for each field of data in a table. So for each customer record there may be one or more promotions with one or more conference attendances in response to the promotions. The collection of related records constitutes a case. For all customers the collection of customer cases is called the case set. Different case sets can be constructed from the same physical data. How the case set is assembled determines how the mining is done. The focus of the analysis could be the customer the promotions or the conference attendances. We could even do the analysis at the company. If the focus is the customer then such attributes as Gender and tenure could be used to predict the behavior of future customers. In our example we can see that the main unit of analysis called the case is the customer and that the promotional detail is contained in a nested hierarchical fashion within the customer. This is illustrated in Figure . In situations where information is nested in a hierarchical fashion as shown in Figure it is necessary to be careful when specifying the case level key in the data mining analysis since this will be used to determine the case base or unit of analysis. Considerations on defining the unit of analysis and examples on identifying the key to define the case base are taken up in Chapter 5. 5 Modeling Data Information is the enemy of intelligence. Donald Hall In the recent past there has been a growing recognition that we are suffering from what has sometimes been called a data deluge. In Chapter 2 we outlined a data maturity hierarchy which suggested that we turn data into intellectual capital through successive and successively sophisticated refinements. Data are turned into information .
