I have a situation where I have a parameter in ssrs that contains only a single value. When that value gets passed over in the mdx query it allows the results to be filters. The values are directly linked to a dimension in the tabular model. However the tabular model only contains ( null, black, blue, red). I can easily get results when the parameter is black, blue or red but I need the results for "Colors" which is a top of the house values that requires us to display the results for all three colors. Any ideas?
Code
Select
Non Empty
{ ( Measures.TotalColors]} on columns
,Non Empty
{
[DifferentColors].[Color2].[Color2].allmembers
}
Dimension Properties
Member_Caption
,Member_Unique_name
on Rows
From [Colors]
Result
Color2 TotalColors
null 100
black 10
blue 23
red 11
When the parameter is black then it needs to show 10 and when its blue then it needs to show 23. This is easy using parameters.
However I need the following result when I select "Colors" which should bring in all the values in the dimension.
Intended Result
Color2 TotalColors
Colors 144
You could simply aggregate data on higher level for all member, however this will not give you Colors
Select
Non Empty{ ( Measures.TotalColors]} on columns,
Non Empty{[DifferentColors].[Color2].[All]} on Rows
From [Colors]
Or if you want to show Total additionally to list of colors you have to introduce calculated dimension member:
WITH MEMBER [DifferentColors].[Color2].[Color2].[Colors] AS
SUM([DifferentColors].[Color2].[Color2].MEMBERS, Measures.TotalColors)
Select
Non Empty{ ( Measures.TotalColors]} on columns,
Non Empty{[DifferentColors].[Color2].[Color2].allmembers} on Rows
From [Colors]
Related
I have a SSAS DSV similar to following structure:
Id Type Special
1 A 1
2 B Null
3 A Null
4 C 1
5 C Null
I built a dimension for this DSV including one attribute for Type.
Then I have in my cube three measures
Measure1: Count of rows
Measure2A: Sum of Special
Measure2B: Count of non-empty values for Special
Finally in Excel, I display data as following:
Rows --> Type attribute
Values --> Measure1 / Measure2A / Measure2B
When I look at the results, everything is correct.
For instance, I get a count of 1 for measure2A and measure 2B for row = C
BUT when I attempt to drill through for related cells, instead of getting 1 row, I get 2 (the ones where type = C without considering the value of Special)
I guess I am doing something wrong in my design of the cube but cannot understand what.
When determining what rows to show in drillthrough SSAS only considers the dimension context not which detail rows have a non null measure value.
You could add a new dimension on the Special column and add that dimension as a filter to your PivotTable.
Or you could install ASSP and construct a custom rowset action that fires an MDX query which does a NON EMPTY on your measure.
http://asstoredprocedures.codeplex.com/wikipage?title=Drillthrough&referringTitle=Home
What I want to do is generate a report containing an overview of gains and losses (of contracts). For example:
Year | contract_gains | contract_losses
_______________________________________
2015 | 10 | 2
2016 | 15 | 4
Showing the gains is quite easy because I can just count distinct contracts (which is the aggregator for the measure value) with a start period.
SELECT
{[contract_start_date].[year].MEMBERS}
ON ROWS,
{[Measures].[value]}
ON COLUMNS
FROM Cube
Showing the losses seperately is also easy because I can do the same with the second date dimension.
SELECT
{[contract_end_date].[year].MEMBERS}
ON ROWS,
{[Measures].[value]}
ON COLUMNS
FROM Cube
But what I want to do is generate a report containing both of the values in a single report. Sadly I have no idea how I can do this.
A little slow method, going cell by cell. Does this work for you -
WITH MEMBER [Measures].contract_losses AS
(
GENERATE
(
[contract_start_date].[year].CURRENTMEMBER,
FILTER
(
[contract_end_date].[year].MEMBERS,
CStr([contract_start_date].[year].CURRENTMEMBER.MEMBER_VALUE) = CStr([contract_end_date].[year].CURRENTMEMBER.MEMBER_VALUE)
)
).ITEM(0)
,
[Measures].[value]
)
MEMBER [Measures].contract_gains AS
[Measures].[value]
SELECT
NON EMPTY {[contract_start_date].[year].MEMBERS}
ON ROWS,
{[Measures].contract_gains, [Measures].contract_losses}
ON COLUMNS
FROM [Cube]
I'm looking for a solution to create sums of +- 10 scores and targets of a product over 6 different dimensions. There are some more i won't bother you with. Of every dimension I need a total. For example
SalesPeriod. Product: Bikes. Dimensions: bmx, size, colours, with bars etc. Targets: 1,2,3,4,5. Scores:1,2,3,4,5.
So 10 totals for bmx bikes with size x, colour red and bars, and 10 totals for bmx bikes, size x, colour red etc etc.
However, every score needs to be calculated only when none of the underlying values is a null. For example score 1 contains a null then no calculation, but score 2 does not contain a null thus should be calculated.
At this point the calculation is done via a case statement which basically checks the values of within each column/score and only calculates the total when the count of scores is equal to the expected rows.
The calculation requires a lot of cpu and with a larger dataset this is very inefficient and it simply takes too long.
I'm looking for a solution that will be much more effecient. What could be my best option to try?
You can filter (or first group by) the products with Non Null values only first by using your same count method. I don't think there is any other method.
SELECT columnid, SUM(column1)
FROM table
GROUP BY columnid
HAVING COUNT(column1)=COUNT(*);
Then you can join it on columnid with another similar query on another columnN as well.
(I'm not sure if understood your problem completely, but you basically want an efficient query with sum(scores) and sum(targets) only when they are not null? or only when they are both not null? or only scores? or only targets?)
I've been building an MDX query using excel's powerpivot. I connect to my cube, drag and drop Measures /Dimensions and my query has been working just fine. Up until I try to pull different dimensions.
A simple version of my query:
SELECT
NON EMPTY { [Measures].[EP Projected Impressions] } ON COLUMNS,
NON EMPTY { ([EP Hierarchy].[EP Tactic ID].[EP Tactic ID].ALLMEMBERS ) } ON ROWS
FROM [MI_Cube]
This will return:
(EP Tactic ID) (EP Projected Impressions)
1 10
2 20
3 30
4 40
5 50
Now when I try to pull in date information for each tactic from the Time dimension it just gives me a copy of the above results with each time dimension member.
Example query:
SELECT
NON EMPTY { [Measures].[EP Projected Impressions] } ON COLUMNS,
NON EMPTY { ([EP Hierarchy].[EP Tactic ID].[EP Tactic ID].ALLMEMBERS * [Time].[Fiscal Year].[Fiscal Year].ALLMEMBERS ) } ON ROWS
FROM [MI_Cube]
Results:
(EP Tactic ID) (EP Projected Impressions) (Fiscal Year)
1 10 FY2015
1 10 FY2014
1 10 FY2013
1 10 FY2012
1 10 FY2011
2 20 FY2015
2 20 FY2014
2 20 FY2013
2 20 FY2012
2 20 FY2011
etc....
Does this mean that I cannot pull the Time.FiscalYear dimension for each TacticID? Or do I need to restructure my query? EP Hierarchy has lots of dimension members I can pull successfully, but when I try to pull anything from EP Hierarchy and Time my results get multiplied instead of combined.
Thanks for any advice, trying to wrap my head around cubes and mdx queries.
It seems that you are simply missing a relation between the fact table holding the [EP Projected Impressions] member, and the dimension table holding your [Time] dimension.
By adding a relation between a foreign key on the fact table and the primary key on the dimension table, your measures should get correctly filtered by any attributes you slice on the dimension.
Thank you for the responses, it turns out the measure I was using was not connected to the time dimension. Apparently that was an expected behavior, after trying different measures I am getting the results I was expecting.
Anyone have advice on how to build an average measure that is dynamic -- it doesn't specify a particular slice but instead uses your current view? I'm working within a front-end OLAP viewer (Strategy Companion) and I need a "dynamic" implementation based on the dimensions that are currently filtered in the data view.
My fact table looks something like this:
Key AmountA IndicatorA AmountB Other Data
1 5 1 null 25
2 6 1 null 52
3 7 1 2 106
4 null 0 4 108
Now I can specify a simple average for "[Measures].[AmountA]" with "[Measures].[AmountA] / [Measures].[IndicatorA]" which works great - "[IndicatorA]" sums up to the number of non-null values of "[AmountA]". And this also works great no matter what dimensions are selected in the view - it always divides by the count of rows that have been filtered in.
But what about [AmountB]? I don't have a null indicator column. I want to get an average value of [AmountB] for whatever rows have been filtered in for my current view. If I try to use the count of rows as a simple formula (psuedo-code "[Measures].[AmountB] / Count([Measures].[Key])") I get the wrong result, because it is counting all the null rows in the average.
So, I need a way to use the AVG function to specify the average of [AmountB] over the set of "whatever rows I'm currently filtering in, based on whatever dimensions I'm currently using". How do I specify this dynamic set?
I've tried several different uses of the AVG function and they have either returned null or summed up to huge numbers, clearly not the average I'm looking for.
Thanks-
Matt
Sorry, my first suggestion was wrong. If you don't have access to OLAP cube you can't write any mdx-query for this purpose (IMHO). Because, you don't have any detailed data (from your fact table) in this access level and you can use only aggregated data and dimensions from your cube.
Otherwise (if you have access to olap db), you can create this metric (count of not NULL rows) in your measure group and after that use it for AVG calculation (as calculated member in your cube or in section "WITH" in your mdx-query).