The Process Result transform represents the final output or result of the data cube (ETL process).
This transform doesn't do any data processing but it allows you to configure the measures and hierarchies that will be made available to downstream items such as metric sets.
1. Data Cube Elements
Click the Process Result transform to see the Data Cube Elements panel, which shows the list of output measures and hierarchies for this data cube (ETL process). Measures and hierarchies are color-coded differently.
1.1. Hide elements
You can hide a measure or hierarchy from the output by clicking its grey minus icon on the very right. The measure or hierarchy will be listed under a HIDDEN section and you can easily unhide it by clicking its plus icon.
A hidden measure or hierarchy is hidden from the data cube output but will still be available for subsequent linking in hierarchy keys (e.g. if you need to use the data cube later to define a hierarchy).
1.2. Edit elements
You can access additional options related to a specific measure or hierarchy by clicking the edit icon on the right.
The Edit Data Cube Output Element panel will open, where you can change the Caption, Description, Supported Aggregators, and Unique Name of the element.
You can change the element type if the data the supports being both a measure and a hierarchy. For example, edit the OrderQty measure.
1.2.1. Replacing with a hierarchy
Columns such as ProductID are referred to as implicit hierarchies. You can add value to your data cube by replacing such columns with multi-level hierarchies.
For example, to replace the ProductID column with an existing Product hierarchy, click the Edit icon on the right of the ProductID column. This opens the Edit Data Cube Output Element dialog, which shows the available hierarchies in the current project you can use to replace the ProductID column. Find your Product hierarchy, expand to see its levels, and then drag the hierarchy onto the drop region as shown in the figure below. You can also drag the lowest level of the Product hierarchy instead.
In a similar way, you can replace an OrderDate column with a time dimension hierarchy.
1.2.2. Formatting values
You can define the format the way measure values appear in a data visualization. This format will be used as a default, when no other format is indicated on the metric set or dashboard.
|Format Type||Format String||Displayed Text|
|Numeric with 5 decimal places||N5||80,487,704.17919|
|Currency with 2 decimal places||C2||$80,487,704.18|
|Percent (multiplied by 100) with 0 decimal places||P0||8,048,770,418%|
|Exponential/scientific with 2 decimal places||E2||8.05E+007|
|Custom numeric (1 non-zero decimal place)||0,0.#||80,487,704.2|
|Custom numeric (thousands)||#,0,K||80,488K|
|Custom numeric (millions with 1 decimal place)||#,0,,.0M||80.5M|
Double-click the Process Result transform to see its configuration dialog (or use the context menu).
Uncheck any columns which you don't need to be part of the data cube output. This will completely remove the column from the data cube and will make the column unavailable for subsequent linking in hierarchy keys (e.g. if you need to use the data cube to build a hierarchy).
Select the Process Result transform on the canvas and then click Data Preview to see a preview of the data output generated by this data cube.