Data View Fields
System Administration -> Data Services -> Setup -> Data View Fields
The purpose of a Data View is to create a list of values to be used in, for example, Selection Panes.
Important: There are new validation rules that apply when designing a template in template version one. With this new validation process, you are unable to save a Template sheet that does not include a Data View field name.
A Data View can be designed in a number ways, enabling most types of lists to be created:
- Autogenerated
- Custom list using SQL
- Static list with fixed values
- Object Values list
At the top right of the screen, select which data view you want to configure. The data view must be published to a client to be visible in the drop-down. Bizview will then execute the data view and retrieve what fields the data view will return. These fields are listed at the far left section of the screen.
You can select which fields from the data view should be returned as fields from the data view. For example, the underlying query can contain more fields than the data view will return. De-select the fields you do not want the data view to return. A field can in general be one of two things: a measure (number), or an attribute/dimension. Attributes can be grouped into what are called "dimensions".
Select a field and configure meta-data regarding the field.
The Property Area contains the following fields:
Field | Description | Example | Note |
---|---|---|---|
Dimension/Measure | Choose if the field is a dimension or a measure. | ||
Display Text | Descriptive text. | What the end-user will see when viewing data from the data view. | |
Dimension | If the field is an attribute, you can also group this attribute into a dimension. | ||
Aggregate Function | If the field is a measure you can define the display format and the aggregate function. |
Select Save to save the settings.
If you change the SQL-statement returning the data to the data view, and there are fields defined in the Data View Fields editor, that no longer is returned by the SQL-statement, you will see a small indicator to the left of the name of the field. If you want to remove these fields from the meta-data definition, select Clean up from the top-left of the screen.
Hierarchies
A hierarchy is a representation of the fields that makes it easy and intuitive for the end-user to navigate down through the hierarchy structure. An example can be a structure of Product Groups > Products, or Year > Quarter > Month.
The data view only returns flat data. But an analytical report can internally restructure the flat data into hierarchies. But to be able to know how the different fields are related to each other the analytical report must get meta-data about these relations. This is the objective of the far right section of the screen where one or many hierarchies can be defined.
The following example is based on a scenario with a data view returning three separate fields: Year, Quarter, and Month.
Select Add Hierarchy at the top of the Hierarchies section. First, specify the hierarchy by renaming "New Hierarchy". This text will be visible to the end-user. A good example is to describe the hierarchy levels in the name, such as Year > Quarter > Month.
Then drag-and-drop the fields you have in the field list at the far left, into the hierarchy (white box). Start with the top-level field (Year), then the next level (Quarter) etc.
You should also assign the hierarchy to a dimension. In the hierarchy definition you can select a dimension to assign the hierarchy to.
You can preview the data view structure as the end-user will see the structure in an analytical report by selecting Preview at the far right of the screen.
Important: Meta-data for a data source based on an SSAS database is not possible to configure here. This should instead be configured in the SSAS database.
Additional Information
Usage
The Data View(s) created can be used in the following places in Bizview
- Selection Pane Lists, use Data View in the Script parameter to populate the list
- HTML dashboard design
Also see the Functional Whitepaper Data Views