TAILIEUCHUNG - Pro SQL Server 2008 Analysis Services- P2

Tham khảo tài liệu 'pro sql server 2008 analysis services- p2', công nghệ thông tin, cơ sở dữ liệu phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | CHAPTER 2 CUBES DIMENSIONS AND MEASURES Figure 2-16. Selecting a different set of dimension members To further analyze the results we may drill into the date hierarchy to see how the numbers compare by quarter or month. We could also compare these sales results to the sales of other products or number of customers. Maybe we d like to look at repeat customers in each area is France outperforming Italy on attracting new customers bringing back existing customers or both . All these questions can be answered by leveraging various aspects of this cube. Incidentally selection of various members is accomplished with a query language referred to as Multidimensional Expressions or more commonly MDX. You ll be looking at MDX in depth in Chapter 9. A question that may have come to mind by now Are measure values always added Although measures are generally added together as they are aggregated that is not always the case. If you had a cube full of temperature data you wouldn t add the temperatures as you grouped readings. You would want the minimum maximum average or some other manner of aggregating the data. In a similar vein data consisting of maximum values may not be appropriate to average together because the averages would not be representative of the underlying data. Types of Aggregation OLAP offers several ways of aggregating the numerical measures in our cube. But first we want to designate how to aggregate the data either additive nonadditive or semiadditive measures. 31 CHAPTER 2 CUBES DIMENSIONS AND MEASURES Additive An additive measure can be aggregated along any dimension associated with the measure. When working with our sales measure the sales figures are added together whether we use the date dimension region or product. Additive measures can be added or counted and the counts can be added . Semiadditive A semiadditive measure can be aggregated along some dimensions but not others. The simplest example is an inventory which can be added across warehouses .

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