Data Modeling Techniques for Data Warehousing phần 2

tích lũy và củng cố các dữ liệu từ các nguồn khác nhau, và bằng cách giữ dữ liệu lịch sử này trong kho, thông tin mới về kinh doanh, đối thủ cạnh tranh, khách hàng, nhà cung cấp, hành vi của các quá trình kinh doanh của tổ chức, vv, có thể được công bố. | accumulating and consolidating data from different sources and by keeping this historical data in the warehouse new information about the business competitors customers suppliers the behavior of the organization s business processes and so forth can be unveiled. The value of a data warehouse is no longer in being able to do ad hoc query and reporting. The real value is realized when someone gets to work with the data in the warehouse and discovers things that make a difference for the organization whatever the objective of the analytical work may be. To achieve such interesting results simply reengineering the source data models will not do. Chapter 2. Data Warehousing 7 8 Data Modeling Techniques for Data Warehousing Chapter 3. Data Analysis Techniques A data warehouse is built to provide an easy to access source of high quality data. It is a means to an end not the end itself. That end is typically the need to perform analysis and decision making through the use of that source of data. There are several techniques for data analysis that are in common use today. They are query and reporting multidimensional analysis and data mining see Figure 1 . They are used to formulate and display query results to analyze data content by viewing it from different perspectives and to discover patterns and clustering attributes in the data that will provide further insight into the data content. Figure 1. Data Analysis. Several methods of data analysis are in common use. The techniques of data analysis can impact the type of data model selected and its content. For example if the intent is simply to provide query and reporting capability a data model that structures the data in more of a normalized fashion would probably provide the fastest and easiest access to the data. Query and reporting capability primarily consists of selecting associated data elements perhaps summarizing them and grouping them by some category and presenting the results. Executing this type of capability

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