The Unified Dimensional Model (UDM) lets you define an end-user model over its base data-access layer, providing a comprehensible view of the data that lets users quickly understand, analyze, and act on business information. Here's a quick overview of the capabilities the end-user model supports.

Dimensional model. The UDM presents data to the user through a dimensional model of measures and dimensions. The dimensional model uses easy-to-understand, business-oriented names rather than the system-oriented names that commonly reside in the underlying data sources.

Hierarchies. In the UDM, a dimension can contain an attribute for each column of the underlying dimension table. It can also contain additional user hierarchies, which capture a user's common drill-down paths and reflect relationships in the underlying data. For example, a Product hierarchy might contain the levels Category, SubCategory, and SKU because the user commonly drills down through those levels.

Formatting. You can use the UDM to define the data formatting the client uses, such as "Sales shown in red if < 90% of Quota."

Categorization. In the UDM, users naturally apply categorizations to their data—for example, specifying that certain attributes are about an employee's personal details and that another attribute is an email address. The UDM supports these categorizations by letting you place dimensions, attributes, and other objects into semantically meaningful categories, enabling more intelligent usage within a client tool. You can also group objects into folders that are meaningful to the user (such as Customer\Demographics), letting the reporting tool display large numbers of attributes in a manageable way.

Time intelligence. The UDM has built-in knowledge of time, including different calendars (e.g., natural, fiscal, reporting, ISO8601). Thus, the model can include a time dimension, providing a set of attributes that define details of each day.

Translations. To support organizations that have international users, the UDM lets you translate metadata into any language so that a client connecting from a particular locale can see all metadata in the appropriate language. In addition, an attribute in the UDM can map to different elements, letting you translate data into different languages.

Perspectives. A UDM might include tens of measures and dimensions, with each dimension including tens or even hundreds of attributes. Generally, however, users involved in a particular task don't need to see the entire model. So, a UDM can contain many perspectives, each presenting a specific subset of the full model.

Attribute semantics. A UDM provides additional semantics for each attribute to make information more readily consumable. For example, showing every distinct value for a numeric attribute often isn't useful. When a user wants to see Sales by Product Price, viewing all the different prices (e.g., $9.97, $10.05, $10.10) is much less useful than seeing sales per price range (e.g., <$10, $10-$15, $16-$20). The UDM lets you automatically break attribute values into such ranges using various criteria. You can also define default ordering (e.g., displaying priorities in the order of High, Medium, then Low) and default names versus keys to use for an entity.

Key Performance Indicators (KPIs). The UDM lets you define KPIs to enable more understandable groupings and presentation of data.

Named sets.A UDM can define named sets of entities of interest to the user, such as the top 10 customers (by volume of sales) or the most important food products.

Integration with data mining. The UDM is tightly integrated with data-mining technology, letting users mine data and use the discovered patterns for prediction.

Default aggregation. The UDM defines a measure's default aggregation, which can be Sum, Count, Distinct Count, Max, Min, or Average. In addition, the UDM can define the aggregation as semi-additive or based on the type of account, such as Income or Expense.

Closing the loop. The UDM not only presents data to users in ways they can understand, it also makes it easy for them to take action based on the data they see. The UDM lets users change data in both measures and dimensions. And it lets users define actions to take, such as navigating to a particular URL or executing a specified report, based on the data the user is viewing.