Show items with no data on rows | SSAS , MDX - ssas

Working on a task that required to bring all a dimension’s data to the Pivot Table(Excel Sheet) even if they are not related to the fact.
first I was able to do it by using the option “PivotTable Options” -> “Display” -> “Show items with no data on rows” from Excel. The problem here is that using this option is going to affect the other dimensions and the requirement is to only this work for the Student dimension only and the user doesn’t like to keep changing the option back every time. then I found this solution using SCOPE, below, but just like above I could not find an away to just have the scope ignore the logic if any other dimension added so the data does not get duplicated.
SCOPE ([Program].[Program Hierarchy].MEMBERS, [Measures].[Number of Students]);
THIS = IIF(ISEMPTY([Measures].[Number of Students]), 0, ([Measures].[Number of Students]));
END SCOPE;
So is there something that I can add the SCOPE above to just work in the program dimension and get ignore/ skip and work as normal if any other dimension added to the pivot table?
Any suggestion will be appreciated.

Lets suppose that for Dimension1 ,attribute1, and the attribute "Value 1", you had nothing in Fact, so this is removed from the result, now you forced Excel to display it by selecting the option. When you add another dimension's attribute lets say Dimension2.Attribute1, since "Value 1" had nothing in Fact, therefore Cube will not understand which value of of Dimension2.Attribute1 is to be displayed in front of Dimension1.Attribute1, therefore it will display all its values. So if we have 3 values in Dimension2, attribute 1 then "Value 1" will be repeated three times. Now with Excel you cannot solve the issue, however it might just be possible to write an MDX query that works.
Edit: Query Added.
The below sample query is based on AdventureWorks, the first sample shows that the result has some nulls, if i un-comment the "non-empty" all null values will vanish, go ahead try it.
select [Measures].[Internet Sales Amount] on columns,
--non empty
[Product].[Subcategory].[Subcategory]
on rows
from
[Adventure Works]
Result without non empty
Now lets add another dimension to the query. Notice that the null value for the first row(Bib-shorts) is now repeated for all values of the second dimension, Since cube has no way to determine which value to display.
select [Measures].[Internet Sales Amount] on columns,
--non empty
([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].[Calendar Quarter of Year])
on rows
from
[Adventure Works]
Result
Now the above result shows the issue you are facing. What we now need to do is whenever there is a null value we dont need the individual members of the second dimension, rather a place holder to satisfy the tuple, will work.
In the query below I have two tuples
1) for the not null data-points. Here we display the actual member of the second dimension.
2) for the null data-points, here we use ".defaultmember" which basically means that the second dimension will behave as it was never selected. Have a close look at the second dimension it says "All Period"
select [Measures].[Internet Sales Amount] on columns,
--non empty
{filter(([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].[Calendar Quarter of Year]),[Measures].[Internet Sales Amount]>0),
filter(([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].defaultmember),[Measures].[Internet Sales Amount]=null)
}
on rows
from
[Adventure Works]
Result:

Related

Simple Calculated Member Running for Forever - MDX

I am facing very strange issue with MDX (SSAS 2014), on which simplest calculated member is taking forever to execute. Could someone please help me to understand why i am facing this issue. If i not use calculated member everything works fast and result comes in seconds. When i remove Producer attribute, query performances well.
Below is the complete query.
WITH
MEMBER Measures.AsOfDate AS ("[Policy Effective Date].[Year-Month].[Date].&[2018-01-04T00:00:00]")
MEMBER Measures.YTDPremium AS AGGREGATE (YTD(STRTOMEMBER(Measures.AsOfDate)), [Measures].[Written Premium])
SELECT NON EMPTY
{
Measures.YTDPremium
} ON COLUMNS, NON EMPTY
{
(
[Program].[Program Name].[Program Name]
,[Insuring Company].[Insuring Company Name].[Insuring Company Name]
,[Line Of Business].[Line Of Business].[Line Of Business]
,[Producer].[Producer Name].[Producer Name]
)
} ON ROWS
FROM [Premium]
Try understand what the following part does in your query
NON EMPTY { ( [Program].[Program Name].[Program Name]
,[Insuring Company].[Insuring Company Name].[Insuring Company Name]
,[Line Of Business].[Line Of Business].[Line Of Business]
,[Producer].[Producer Name].[Producer Name]
) } ON ROWS
In the above MDX you are telling the server to take a cross product of all values of "Programs", "Line Of Business" and "Producer Name". So lets say you have 4 values of programs , 3 values of line of business and 2 values of producer name. The total combinations are 4*3*2=24
Now the "Non empty" removes any combinations that are not present in your dataset. This is done by removing all rows that have "Null" value in column value.
Your measure is returning value irrespective if that combination exists or not. You can modify your Calculatedmeasure to return value only in the case if the combination is valid. This can be achived by checking an actual measure for that combination
Edit: based the below example is based on the comment
In the below example i am trying to get the internet sales amount categories and components
select
{ [Measures].[Internet Sales Amount] }
on columns,
(
[Product].[Category].[Category],
[Customer].[Country].[Country]
)
on rows
from [Adventure Works]
Result
Now add "Non empty" to the query and observe the results.
Results
Now lets add calculted measure that returns "hello". Notice how the non empty clause is ineffective.
Now modify the code make the calculated measure check other measures for null
with member measures.t as
case when [Measures].[Internet Sales Amount] = null then null else "hello" end
select
{ [Measures].[Internet Sales Amount] ,measures.t }
on columns,
non empty
(
[Product].[Category].[Category],
[Customer].[Country].[Country]
)
on rows
from [Adventure Works]
Result
The bottom line: Because of cross product your result is so huge that SSAS is having hard time handling it.

Non-empty previous value - MDX

I am using Performance Point Dashboard Designer 2013 and SharePoint Server 2013 for building dashboards. I am using SSAS2012 for Cube.
I have a scenario similar to the one illustrated by figure below. I am required to find Previous Non-Empty value for purpose of finding Trends.
Measure: [Quota]
Dimension: [Date].[Calendar Date].[Date]
The script ([Measures].[Quota], [Date].[Calendar Date].PrevMember) gives you a previous date. Lets say for date 27-Jan-13 whose Quota value is 87, it returns 26-Jan-13 which has null value. I want it to return 21-Jan-13 that has some Quota value. And for date 21-Jan-13, I want to return 15-Jan-13.
I wonder if this is possible.
Thanks,
Merin
After long searches and hits & trials and so on, I think I invented a solution of my own for myself.
Following is the script for my Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
Explanation
The number 15 means it will look for non-empty measures up to 15 siblings.
Now we know up to how many siblings to traverse back, in this case 15.
Lets find 15 previous siblings (both empty and non-empty) excluding current member.
(LastPeriods(15, [Date].[Calendar Date].PrevMember)
Since it will yield both empty and non-empty members, lets filter out empty members in terms of measure [Quota]. If we don't specify measure here, it will use default measure whatever it is and we may not get desired result.
Nonempty(LastPeriods(15, [Date].[Calendar Date].PrevMember),[Quota])
We may have several members in the output. And we will choose the last one.
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
)
So far, the script above gives previous non-empty member. Now we want to implement this member for our measure [Quota].
Hence we get the script below ready to create a Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
You can use recursion to define this.
The following query delivers something similar for the Adventure Works cube:
WITH member [Measures].[Prev non empty] AS
IIf(IsEmpty(([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Prev non empty]),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])
), format_String = '$#,##0.00'
SELECT {[Measures].[Internet Sales Amount], [Measures].[Prev non empty]}
ON COLUMNS,
non empty
Descendants([Date].[Calendar].[Month].&[2007]&[12], [Date].[Calendar].[Date])
ON ROWS
FROM [Adventure Works]
WHERE [Customer].[Customer].&[12650]
You would have to replace the name of the date hierarchy, as well as the measure name from Internet Sales Amount to Quota in the recursive definition of the measure Prev non empty.

MDX currentmember/IS inconsistent?

I have three queries to filter by a member using the currentmember function. When the filter is applied to the hierarchy that has the member I want to filter by, I can match the members using the IS operator and get the correct result. It does not work though when the filtered set and the member are in different hierarchies. Yet, I can get the filtered results correctly for the second case if instead of objects comparison I just do a caption comparison. The examples use the AdventureWorks database.
This query is working as expected with the IS operator:
select non empty [Measures].[Reseller Sales Amount] on 0,
Filter (NonEmpty({[Geography].[Country].[Country].ALLMEMBERS * [Geography].[City].[City].ALLMEMBERS}), [Geography].[City].Currentmember IS [Geography].[City].&[Seattle]&[WA]) on 1
from [Adventure Works]
This one uses a caption comparison (different result, as expected)
select non empty [Measures].[Reseller Sales Amount] on 0,
Filter (NonEmpty({[Geography].[Country].[Country].ALLMEMBERS}), [Geography].[City].Currentmember.MEMBER_CAPTION = 'Seattle') on 1
from [Adventure Works]
This one though, which should produce the same result as the previous query, does not return anything:
select non empty [Measures].[Reseller Sales Amount] on 0,
Filter (NonEmpty({[Geography].[Country].[Country].ALLMEMBERS }), [Geography].[City].Currentmember IS [Geography].[City].&[Seattle]&[WA]) on 1
from [Adventure Works]
Thanks.
In fact, this is a bit strange. For me, the most surprising result is the second one. No reference in the set to be filtered to the city, and nevertheless, a filter is applied. I would think the reason for the second result is that somehow "implicit overwrite" kicks in.
And probably, the second and third case are treated differently as the optimizer somehow choses different ways to interpret the statement. Normally, string operations like the reference to caption are less efficient than the IS operator which works on object identity.
It looks like most comments confirm that the result of the second query is a bug. Some more comments here in this other thread

Filtering a Measure (or Removing Outliers)

Say I have a measure, foo, in a cube, and I have a reporting requirement that users want to see the following measures in a report:
total foo
total foo excluding instances where foo > 10
total foo excluding instances where foo > 30
What is the best way to handle this?
In the past, I have added Named Calculations which return NULL if foo > 10 or just foo otherwise.
I feel like there has to be a way to accomplish this in MDX (something like Filter([Measures].[foo], [Measures].[foo] > 10)), but I can't for the life of me figure anything out.
Any ideas?
The trick is that you need to apply the filter on your set, not on your measure.
For example, using the usual Microsoft 'warehouse and sales' demo cube, the following MDX will display the sales for all the stores where sales were greater than $2000.
SELECT Filter([Store].[Stores].[Store].members, [Unit Sales] > 2000) ON COLUMNS,
[Unit Sales] ON ROWS
FROM [Warehouse and Sales]
I met similar problem when use saiku (backend with Mondrain), as I haven't found any clear solution of "add filter on measure", I added it here, and that may be useful for other guy.
In Saiku3.8, you could add filter on UI: "column"->"filter"->"custom", then you may see a Filter MDX Expression.
Let's suppose we want clicks in Ad greater than 1000, then add the following line there:
[Measures].[clicks] > 1000
Save and close, then that filter will be valid for find elem with clicks greater than 1000.
The MDX likes below (suppose dt as dimension and clicks as measure, we want to find dt with clicks more than 1000)
WITH
SET [~ROWS] AS
Filter({[Dt].[dt].[dt].Members}, ([Measures].[clicks] > 1000))
SELECT
NON EMPTY {[Measures].[clicks]} ON COLUMNS,
NON EMPTY [~ROWS] ON ROWS
FROM [OfflineData]
i think you have two choices:
1- Add column to your fact(or view on data source view that is based on fact table)like:
case when unit_Price>2000 then 1
else 0
end as Unit_Price_Uper_Or_Under_10
and add a fictitious Dimension based on this columns value.
and add named query for New Dimension(say Range_Dimension in datasourceview :
select 1 as range
union all
select 0 as range
and after taht you cant used this filter like other dimension and attribute.
SELECT [Store].[Stores].[Store].members ON COLUMNS,
[Unit Sales] ON ROWS
FROM [Warehouse and Sales]
WHERE [Test_Dimension].[Range].&[1]
the problem is for every range you must add When condition and only if the range is static this solution is a good solution.
and for dynamic range it's better to formulate the range (based on disceretizing method )
2- add dimension with granularity near fact table based on fact table
for example if we have fact table with primary key Sale_id.we can add
dimension based on fact table with only one column sale_Id and in dimension Usage tab
we can relate this new dimension and measure group with relation type Fact and
after that in mdx we can use something like :
filter([dim Sale].[Sale Id].[Sale Id].members,[Measures].[Unit Price]>2000)

MDX Calculating Time Between Events

I have a Cube which draws its data from 4 fact/dim tables.
FactCaseEvents (EventID,CaseID,TimeID)
DimEvents (EventID, EventName)
DimCases (CaseID,StateID,ClientID)
DimTime (TimeID,FullDate)
Events would be: CaseReceived,CaseOpened,CaseClientContacted,CaseClosed
DimTime holds an entry for every hour.
I would like to write an MDX statement that will get me 2 columns: "CaseRecievedToCaseOpenedOver5" and "CaseClientContactedToCaseClosedOver5"
CaseRecievedToCaseOpenedOver5 would hold the number of cases that had a time difference over 5 hours for the time between CaseReceived and CaseOpened.
I'm guessing that "CaseRecievedToCaseOpenedOver5" and "CaseClientContactedToCaseClosedOver5" would be calculated members, but I need some help figuring out how to create them.
Thanks in advance.
This looks like a good place to use an accumulating snapshot type fact table and calculate the time it takes to move from one stage of the pipeline to the next in the ETL process.
Query for AdventureWorks (DateDiff works in MDX):
WITH
MEMBER Measures.NumDays AS
'iif(ISEMPTY(([Delivery Date].[Date].CurrentMember
,[Ship Date].[Date].CurrentMember
,Measures.[Order Count]))
,null
, Datediff("d",[Ship Date].[Date].CurrentMember.Name
,[Delivery Date].[Date].CurrentMember.Name))'
SELECT
NON EMPTY {[Ship Date].[Date].&[63]
:[Ship Date].[Date].&[92]} ON COLUMNS,
NON EMPTY {[Delivery Date].[Date].&[63]
:[Delivery Date].[Date].&[92]}
* {[Measures].[NumDays]
, [Measures].[Order Count]} ON ROWS
FROM [Adventure Works]
Taken from: http://www.mombu.com/microsoft/sql-server-olap/t-can-i-have-datediff-in-mdx-265763.html
If you'll be using this member a lot, create it as a calculated member in the cube, on the Calculations tab if I remember right.