iMIS Analytics is a sophisticated product that creates and maintains a robust data warehouse and eight powerful OLAP cubes in a special analysis database. Most of the product is invisible to you, however, working behind the scenes. If you are using the recommended ProClarity Professional viewer to analyze the data in the cubes, your main exposure to the product is through the iMIS Analytics Briefing Book.
The Briefing Book contains many predefined views of your iMIS data, but sometimes you will want to see information that is not available in one of the predefined views. In these situations, you will want to use the following special features of ProClarity Professional (see your ProClarity Professional tutorial to learn more about these features):
displays more granular details of a chart
When viewing any chart, you can drill down to more granular data for a particular data point by left-clicking the data point. You can also "cross-drill" to other closely related data by right-clicking the data point and choosing the related data type into which you want to drill-down.
creates custom views of your iMIS data
To create your own custom views, you use the Dimensions Tool to define the measures, dimensions, and members that you want to examine. To use the Dimensions Tool effectively, you must understand the following terms:
numeric measurements of business performance
Measures (also known as facts) are the important numerical data in your data warehouse and cubes, such as sales amounts, pledge amounts, quantity on hand, and so on. Measures by themselves are meaningless. Measures are relevant only when viewed in the context of their related dimensions. For example, a measure called Sales Amount means nothing by itself. Sales Amount of what? To make the measure meaningful, you must view it in relation to one or more dimensions, such as Product Class, Organization, Date, and Customer Location. Only by combining the Sales Amount measure with those various dimensions can you create meaningful charts such as Revenue by Country per Calendar Year.
categories of your business for which you need to see measurements
Dimensions are the important categories of your business that give meaning to measures. For example, dimensions such as Product Class and Warehouse are useful categories related to understanding the inventory aspects of your organization, and these dimensions would give meaning to measures such as Cost, Quantity on Hand, and Quantity on Order. Data warehouses and OLAP cubes are often referred to as being multi-dimensional, because you can view a measure as it relates to any combination of related dimensions.
hierarchical sub-categories within a dimension
Each dimension is further divided into a hierarchy of members (also known as levels). For example, a dimension called Product Class might contain a member called All Products, which in turn contains members such as Donorclub, Events, Fundraising Gifts, and Product Sales. The Events member might further contain members such as Fall Conference, Technology Expo, Boston Annual Meeting, and so on.
10.6 Production Release. Updated 9/28/2005 3:49:52 PM
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