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There are two ways that you can connect to data in WebFOCUS BUE. You can upload a Microsoft Excel spreadsheet or CSV file using the Upload wizard, or you can connect to an existing table in a data source of your choice, using the Connect to Data wizard. Both processes begin with identifying and preparing the data that you want to use. Once you have prepared your data, you can upload it or connect to it. After your file or table selection is complete, the wizard shows you the default breakdown of your data into measures, dimensions, and hierarchies.
At similar points during the upload and connect processes, you can access options to transform your data beyond the default settings. This includes grouping data into hierarchies, joining multiple tables into a cluster to create more fields and expand the scope of a synonym, editing geo roles and geo encoding to prepare the synonym for use in mapping and location analysis, data profiling and statistical analysis, changing columns or groups of columns into rows, and creating new or editing existing measures, dimensions, hierarchies, and attributes.
Once a synonym is complete, you can upload it to a target adapter environment or append it to an existing synonym. You can also save it as a template to allow repeated transformations if the same file is uploaded again in the future.
When you upload or connect to data in WebFOCUS BUE, you create a synonym that can be used to build analytical content. Synonyms define unique names (or aliases) for each object that is accessible from the server. Synonyms are useful because they hide the underlying data source location and identity from client applications. They also provide support for extended metadata features of the server, such as virtual fields and additional security mechanisms. Depending on the structure of the synonym that you are creating, the data inside a synonym is typically broken down into measures, dimensions, hierarchies, and attributes.
A measure is a numeric value, such as gross profit or cost of goods sold, that you may want to aggregate. All numeric values that can be summed are measures. Numeric fields that cannot be summed, such as product number and miles per gallon, are not treated as measures. Instead, they may be used in the same way as dimension fields to analyze measures. It is up to you to understand your data and determine whether each numeric field can be summed. Related measures can be organized into measure groups. For example, gross profit and cost of goods sold can be part of a sales measure group.
A dimension is a way to categorize data. You can use a dimension to analyze and compare measures. Generally, any field that is not a measure, usually an alphanumeric field such as product, is a dimension. Dimensions can be organized into hierarchies to define the relationships between the fields in the hierarchies. For example, a geography hierarchy can contain continent, country, state, and city dimensions. You can also define dimension fields that are not part of a dimension hierarchy.
You can assign dimension attributes to any dimension field, whether or not it is in a hierarchy. When applied to a field, attributes provide supplementary information that can be used for analysis or display. For example, in a geography hierarchy, which includes country, state, and city dimensions, population information can be assigned as an attribute of the city dimension. It is up to you to determine whether a measure as an attribute is useful. It depends on the design of the data source.
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