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Understanding the Business Model

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Understanding the business model is the first step in developing a usable data model for decision support—a model that business analysts will inherently understand and that will answer meaningful questions correctly. This requires breaking down the business into several components to answer the following questions:

• What kinds of business questions are analysts trying to answer?
• What are the measures required to understand business performance?
• What are all the dimensions the business operates under?
• Are there hierarchical elements in each dimension and what are the parent-child relationships that define each hierarchy?

When you can answer these questions, you can use the Administration Tool to build a valid, usable, and intuitive business model.

Identifying the Factual Measures

Facts are the business measures to be analyzed. These are typically additive items, such as sales dollars and units sold. Each measure will have its own aggregation rule, for example, SUM, AVG, MIN, MAX, or COUNT. Often a business will want to compare values of a measure over time and will need a calculation to express the comparison, as in, for example, a change or percent change.

Identifying the Dimensions of a Business

A business uses facts to measure performance by well-established dimensions, for example, by time, product, and market. Every dimension has a set of descriptive attributes. The best method to identify dimensions and their attributes is to talk with the analysts in the organization who will use the data. The terminology they use and understand is important to capture.

Identifying Hierarchical Relationships Between Attributes

A hierarchy is a set of parent-child relationships between certain attributes within a dimension. These hierarchy attributes, called levels, roll up from child to parent; for example, months can roll up into a year. These rollups occur over the hierarchy elements and span natural business relationships.

Understanding the hierarchies is essential to provide the metadata that allows the Siebel Analytics Server to determine if a particular request can be answered by an aggregate that is already computed. For example, if month rolls up into year and an aggregate table exists at the month level, that table can be used to answer questions at the year level by adding up all of the month-level data for a year.

You should identify as many natural hierarchies as possible. As with business questions, some hierarchies are obvious, but some are not and are only known by the end users who interact with particular aspects of the business. You should verify that you understand the hierarchies so you can define them properly using the Administration Tool.

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