CREATING THE DIMENSION
In order to achieve this I have created a dummy dimension, similar to a ‘time utility dimension’ (also known as a ‘date tool’ dimension or a ‘shell’ dimension. I had advice from Chris Webb regarding this, he also referred me the book ‘Expert Cube Development with SQL Server Analysis Services 2008’) and then add a calculated member to it with two values.
We do not need to create a table in our Data warehouse for this purpose; we can create a view some thing like this
CREATE VIEW RevenueAsPositive AS
SELECT 0 AS ID, 'Convert Revenue to Positive' AS Description
UNION ALL
SELECT 1 AS ID, 'Stay Revenue as Negative' AS Description
Now we need to add this view inside our DSV and create a dimension based on this view
Alternatively we can create some thing like this inside our DSV
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So this dimension has two values
1. Convert Revenue to Positive --> 0
2. Stay Revenue as Negative --> 1
This dimension has no relationship with fact table as shown in the figure
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CONFIGURING THE DIMENSION
After creating this dimension now you need to set the properties of the attribute hierarchy
• Set “DefaultMember” to ‘Stay Revenue as Negative’, as below:
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•Set the “IsAggregatable” property to “False”, so there’s no All Member on the attribute hierarchy, as below:
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In the following picture you can see all the revenue figures are negative, which is the default behavior we have defined inside the Analyses Services Cube
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If now the user would like to convert the revenue figures to display as positive, they need to set the report filter to Convert Revenue to Positive as shown in the following figure:
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In order to achieve this functionality you need to use a scoped assignment using MDX that’s something like this:
When the user chooses “Convert Revenue to Positive” than I multiplied all actual measure values by -1, using this MDX:
SCOPE([Convert Revenue To Positive].[Convert Revenue To Positive].&[0],descendants([Dimension POST CODE].[Post Code Structure].[PC Level 2].&[IREV],[Dimension POST CODE].[Post Code Structure].[Post Code],self_and_before),[Measures].[YTD Actuals]
);
This =(([Dimension POST CODE].[Post Code Structure].currentmember)*(-1));
END SCOPE;
SCOPE([Convert Revenue To Positive].[Convert Revenue To Positive].&[0],descendants([Dimension POST CODE].[Post Code Structure].[PC Level 2].&[EREV],[Dimension POST CODE].[Post Code Structure].[Post Code],self_and_before),[Measures].[YTD Actuals]
);
This =(([Dimension POST CODE].[Post Code Structure].currentmember)*(-1));
END SCOPE;
Notice that the “Profit and Loss” values do not change even though the Revenue values have changed to positive. This is achieved through the following SCOPE statement:
SCOPE([Convert Revenue To Positive].[Convert Revenue To Positive].&[0],[Dimension POST CODE].[Post Code Structure].[PC Level 1].&[PL],[Measures].[YTD Actuals]
);
This =(([Dimension POST CODE].[Post Code Structure].&[EEXP])+[Dimension POST CODE].[Post Code Structure].&[IEXP]-[Dimension POST CODE].[Post Code Structure].&[IREV]-[Dimension POST CODE].[Post Code Structure].&[EREV]);
END SCOPE;
Hopefully this will help you if you are trying to build some similar functionality.
Finally, I would like to acknowledge and thank Chris Webb for his suggestions and support, thank you Chris.