Visually BI: SSAS part 2

In this 2nd part the topic covered are : add attributes for a dimension, define user hierarchies, setting AttributeHierarchyVisible property, setting  attribute relationship, defining KeyColumns property and NameColumn property,User Hierarchy and Attribute relationships.


The map is here



The map topics are:

.dim file

the definition are here so you have to modify each dim file generated by the cube wizard


identify the slice and dice attributes

rename with friendly names

Cube Project

add attributes for each dim

drag the attributes from data source view to the attributes pane


rename them

with friendly names


define user hierarchies

drag attributes from the attributes pane to the hierarchies pane

the top to bottom (the most granular)


set AttributeHierarchyVisible property

to hide pk (usually)


browse them

Process the dim and then check the hierarchy in the browser


set attribute relationship

to create an attribute relationship drag the Date attribute in the Attribute Relationships tab onto the next-most-granular attribute (Month) and so on

from this





define key with multiple attributes

Ex the quarter calendar key is duplicated, so we need to build in on a combination of key to make it unique (for months too)

KeyColumns property

ex for the Quarter


the 2 keys together will give the necessary unique value

NameColumn property

The multi key need a column to show the name to the user


classify a dimension type

Dimensions and attributes can be classified to introduce new usability features

To classify a dimension, click the Date dimension and select Time from the Type drop-down box (in the Properties window).


User Hierarchy

attributes hierarchy to make easier to navigate



you should drag

· year

· quarter

§ month

· day

to see measure at day level



having a date hierarchy

you drag only it, and then you can navigate it (the struct is already arranged)

Attribute relationships

Attribute relationships allow you to create relationships between dimension attributes, much like foreign key relationships in SQL Server.

performance tuning

the cube id build faster as attributes have a structured relationship

data security

The user can browse more meaningful data


CustomerID (primary key) -> City -> State -> Country


From a State X I’ll see only the City of that state, not city of others state


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