(This is a mock of my actual setup to help me figure out the problem.)
I have one fact table and one dimension table, linked by an id field.
My goal is to make a measure that sums up all "thing_count" (integer) values in my cube.
If the user splits by nothing, it should show the total "thing_count" for all records in the fact table. If it's split by "category_name" from the dimension, it should show the total "thing_count" for each category.
I tried to achieve this by creating a SUM measure in my cube:
It works, but not in the way I intend it to
It always shows (null) unless I drag in the "id" field from the dimension.
Measure only:
Measure and category:
Measure, category, and id:
How can I make the measure show the value without keys needing to be present?
Edit:
For GregGalloway's request (I've edited the names so the screenshots are easier to follow):
One common explanation for this behavior (no aggregation) is that you have inadvertently commented out the CALCULATE; statement in your MDX script in the cube. Please check that statement is still present.
Related
I've been dealing with this issue in various ways throughout my time with this dataset in Tableau.
As you can see, the Total count of properties for each city is including properties that have been successfully filtered out of view. Why? The dyn.RANKED Profitable Investments (grouped) variable on the Filter shelf is an attempt to double down on the same as the first line of the Calculated Field - to ignore the unwanted properties in each city. The view ignores them, but the totals do not.
If the Watershed Property pill is removed from the Rows shelf, then the dyn.NumProps_in_City results shown on the table are each the same as the Totals you see here (i.e., despite the first line of the calculated field, properties that do not meet that opening condition are being counted)...despite the view with the Watershed pill knowing not to show them.
Also if the Watershed Property pill is removed from the Rows shelf, then the dyn.RANKED Profitable Investments (grouped) variable on the Filter shelf suddenly only has one category to choose from (i.e., 'INVEST') if you go to edit the filter. Which would be great since that's the category I care about, but not if the counts are including things that are not in that category despite the filter.
Messing around with Include, Exclude, and Fixed in the calculated field doesn't seem to work here since I can't figure out how to get around various aggregate/non-aggregate and/or ATTR errors no matter where I place them. Plus, my incorrect counts are not suffering from an LOD issue - the LOD is correct - it's an issue of not consistently filtering out the unwanted rows at the desired LOD.
Please advise!
Thanks,
Christian
It seems that dyn.Ranked calculated field calculates the value prior to filtering. This may happen if you have used any LOD calculations in the syntax.
Simply right click such fields on filters shelf and click add to context. This will cause LOD calculations to calculate after the filtering.
see this link, the context filters are above the LOD calculations, in order of precedence; but measure filters are below the LOD calcs. Therefore if measures are used as filters, these have to be added to context so that their order of precedence is above such calculations
I have a cube in SSAS multidimensional mode.
I have created a calculating measure in visual studio called "Total Cost". The formula is:
[Measures].[Unit Cost]*[Measures].[Qty]
It is in the lowest level of granularity (i.e. - the transnational level information has these fields).
The formula works well, as long as I present the data in this same level of granularity (for example, when I create a pivot and the rows are transaction IDs - like the source file)
However, when I present it in an aggregate format (for example - by customer) - then instead of making the calculation and then sum it up, it sum up and then calculate.
Here is what I expected:
Expected results vs. What I get
My understanding, that this is regardless a (correct/incorrect) hierarchy structure. In other words, I expected this calculation to work even without defining any hierarchy between the transaction ID level and the customer level.
I'd appreciate your help!
In your SSAS project ->datasource view, you need to add a named calculation. This would be "[Unit Cost]*[Qty]". Now add this named calculation as a Measure in your Cube. This do the job. This problem was already addressed in the following link.
https://stackoverflow.com/questions/53554284/how-to-multiply-two-measures-prior-to-aggregation/53558733#53558733
I have a requirement where report should show measures as "not applicable" if one selects a attribute which is not linked to that measure Group.
1) unrelateddimesnion= 'false' is not solving my problem because i have few default members.
2) I could able to show measure value as "not applicable " by Writing this MDX statement
([Customer].[customer name].[customer name], [measures].[sales forecast]) = 'not applicable'
but with this i have to repeat the same line for each and every attribute present in the dimension ( and also for each and every measure present in the measure Group)
can someone help me Writing the MDX for entire dimension instead for individual attribute. Thanks in advance.
Kind Regards
Mah
Bad news! An MDX script on your cube can't reference such a sub-cube in a simple way. You may have seen the LEAVES(dimension) function for a scope statement but that won't work when one attribute in a dimension has the [All] level and another has a selection. (That is to say the function returns the leaves of the dimension's key attribute). What you can do is use nested scope statements with the outer one filtering down to the list of measures you want to affect. That will at least save you typing a formula num_attributes * num_measures times. The scope statement may even accept the MEASUREGROUPMEASURES function. (When I last used that it only returned visible measures but that's probably what you want anyway.)
It may be easier to link measure group and dimension and let your data sit on the UNKNOWN member. (Or an explicit dummy member.) Then filters against or slices to real customer hierarchy values will exclude your [Sales Forecast] rows and show it as null. That's not something I've done and it'll have ramifications for error processing and you'll have to allow users sight of the unknown or dummy member. So recommend you play with the idea before you rely on it.
I hope this helps some.
I started working on Qlikview a week back and I am working on this dashboard.
I have a particular requirement which I am not able to achieve:
So, I have a calculated dimension "Categories" added in my script which based on certain conditions tags each name as SLEEPERS,STARS,WEAKLINKS etc.
Now, I have flagged the names based on certain condition which works fine.
The issue is, I want the sum of those flags on the level of calculated dimension CATEGORIES(SLEEPERS, STARS..etc) and my month field.
I am not able to achieve it because, the flag itself is a calculated field so sum of calculated field doesn't work. I tried using aggr, function but it returns zero for all rows. I am not sure why. in the aggr function I use the sum(Aggr(Flag,MONTH,Categories))
Can someone suggest a work around for this? I have attached the screenshot of the report for better understanding of the requirement
As you can see there is a Total added automatically. The Birth Date and Full Name are not hierarchy attributes. They are both from same dimension. I want to show birth date and full name. How to get rid of the Total?
One way to do this is to Compute a calculated member on your DSV. You can name it for example Birth-Name.
To do this
Open your Data Source View
Right click on the dimension name
New name calculation
Name: Birth-Name
expression: birthday+' '+fullname
Add the new field to your dimension
Preview the cube with the new calced member and money measure
In this way you can view your data and the total of all of them together
There are other ways to do this also, but this is the simplest I could think of. The total cannot be totally removed from the cube, as this is what it's real job is. To make aggregations of data.