Building a Prototype

Measures are the numbers you use to gauge your organization's performance. You should choose the critical success factors in your business as your measures. Examples of typical measures include sales revenues, profit margins, and response times.

If you have multiple data sources, you must relate the dimensions and levels of your model to the data source that contains the columns to be used for each measure.

Your model is more effective if your measures are applicable to more than one dimension. For example, if your dimensions are products, locations, and customers, your measures should bridge these dimensions.

To ensure that your users can make period-to-period comparisons and visualize trends over time, choose a time dimension that reflects and synchronizes accounting periods and reporting schedules.

In most cases, your requirements are met by models based on the calendar or fiscal year. Month, Quarter, and Year categories can be supplemented by relative time categories automatically generated by Cognos® Transformer, such as YTD Growth, the percent-growth year-over-year.

If your organization uses particular time periods, such as lunar weeks and months, or three 8-hour shifts per day, Cognos Transformer supports the definition of custom time dimensions. Even if your query objects originate in Framework Manager, you should import the necessary time-related items into Cognos Transformer, and then define your time dimensions there.

You begin by identifying the data sources that contain the data for the model you want to create.

Suppose that information about your customers is stored in a Customers table and information about your products is stored in a Products table. Related tables called Customer_Details and Product_Details provide additional information about customers and products. Order information is stored in two tables called Orders and Order_Details.

In keeping with good design practice, you decide to set up the Customers, Customer_Details, Product, and Product_Details tables as structural data sources, to provide the information that Cognos Transformer uses to build the Customers and Products dimensions in your model.

The information about transactions is stored in the Orders and Order_Details tables. For efficiency, you decide to combine the information in these tables into a single data source called Order_Info.

The Order_Info data source contains the following information, all of which you use to associate sales with particular customers and products:

• The order dates generate categories for the time dimension.
• Data about customers and sales representatives generates the header information.
• The product, order quantity, and sales amount for each line item in an order provide the sales measures.
• The cost of the order and discounts applied to it provide supplementary fact data.