I Tried to create a calculated measure inn my SSAS cube with complex filters as the following:
([Measures].[Amount],[Scenarios].[Scenario Key].&[1],[AccountType],[AccountType].[Account Type].&[Bank],[AccountType].[Account Type].&[Cash],[AccountType].[Account Type].&[NotesReceivable],[JE Type].[JE Type].&[CI],[JE Type].[JE Type].&[NR])
I want to Get the summation of amount value which has:
Scenario Key = 1
Account Type IN ("Bank","Cash","NotesReceivable")
JE Type IN ("CI","NR")
But i Get this measure as Null So can any one can help to solve this?
It's not working because you are doing an intersection of the same dimension hierarchy:
[AccountType].[Account Type].&[Bank],[AccountType].[Account Type].&[Cash]
means in MDX: Account Type = Bank AND Account Type = Cash at the same time.
Just use set of members and SUM function.
Try this one:
SUM(
{[AccountType].[Account Type].&[Bank]
,[AccountType].[Account Type].&[Cash]
,[AccountType].[Account Type].&[NotesReceivable]}
*
{[JE Type].[JE Type].&[CI]
,[JE Type].[JE Type].&[NR]}
,([Scenarios].[Scenario Key].&[1],[Measures].[Amount]))
Explanation:
SUM - aggregate function
Dimension1 filter * Dimension2 filter - gave all combinations
(Dimension3,measure) - filters out single-selected dimensions
Related
I am trying to replicate the following sql statement into MDX so that I can create a calculated member in the cube using the base loaded members instead of having to calculate it outside the cube in the table and then loading it
SUM(CASE WHEN ((A.SALES_TYPE_CD = 1) AND (A.REG_SALES=0))
THEN A.WIN_SALES
ELSE 0
END) AS Z_SALES
I am currently loading SALES_TYPE_CD as a dimension and REG_SALES and WIN_SALES as measures.
I also have a few other dimensions in the cube but for simplicity, lets just say I have 2 other dimensions, LOCATION and ITEM
The dimension has LOCATION has 3 levels, "Region"->"District"->"Store", ordered from top to bottom level.
The dimension has ITEM has 3 levels, "CLASS"->"SUBCLASS"->"SKU", ordered from top to bottom level.
The dimension has SALES TYPE has 2 levels, "SALES_TYPE_GROUP"->"SALES_TYPE_CD", ordered from top to bottom level.
I know that I cannot create a simple calculated member in the cube which crossjoins the "SALES_TYPE" dimension with another dimension to get the answer I want.
I would think that it would be a more complicated MDX statement something like :
CREATE MEMBER CURRENTCUBE.[Measures].[Z_Sales]
AS 'sum(filter(crossjoin(leaves(), [Sales Type].[Sales Type].
[Sales_Type_CD].&[1]), [Measures].[REG_SALES]=0),[Measures].
[WIN_SALES])',
FORMAT_STRING = '#,#',
VISIBLE = 1 ;
But this does not seem to return the desired result.
What would be the proper MDX code to generate the desired result?
I did a bunch of testing with the data and I now know that there is no way I can get the right answer by using MDX alone in this scenario. Like "Greg" and "Tab" suggested, the only way would be to have reg sales as a dimension. Since this is a measure, that is out of the question because of the large number of possibilities for the value which has a data type of decimal (18,2)
Thanks for taking the time to answer the question.
I have a cube with 4 dimensions and I have a measure called Transaction Count. Now I want to calculate the Percentage across all the dimensions for that above measure.
I also have a dimension called Cars. I have the count across all the Cars and now I have defined a calculated measure for calculating the Percentage of each car from the total number of transactions. But it will work only for that particular dimension.
How I can create a single percentage calculated measure which can be used across all the dimensions?
MDX for the calculated measure: (which is working for only Carmake dimension)
CASE
WHEN ISEMPTY( [MEASURES].[Trans COUNT] )
THEN 0
ELSE ([Dim Car Make].[Hierarchy].CURRENTMEMBER,
[MEASURES].[FACT COLORPERFORMANCE COUNT])/
( [DIM CAR MAKE].[CARMAKE].[(ALL)].[ALL],
[MEASURES].[Trans COUNT])
END
I already have a Trancount(1000) measure. Now I need to create a calculated measure Freq % which should be calculated across all the dimensions.
Screenshot -> http://i.stack.imgur.com/iuaQO.jpg (need 10 rep for posting images)
Table 1 in screenshot - you drag and drop the carmake dimension, then both Tran Count and Freq% should be calculated as per CarMake breakdown.
Table 2 in screenshot - you remove CarMake and drag Quality, then both Tran Count and Freq% should be calculated as per Quality breakdown.
Table 3 in screenshot - you remove Quality and drag Brand, then both Tran Count and Freq% should be calculated as per brand breakdown.
The best way i found is using AXIS() to dynamically get the currently used dimension.
with
member Member_Lvl as AXIS(0).item(0).level.ordinal --get the level for next calc
member All_Member as sum(ancestor(axis(0).item(0).hierarchy.currentMember,<yourMeasure>),Member_Lvl )
member Percent_of_All as sum(axis(0).item(0).hierarchy.currentMember,<yourMeasure>) / All_Member
select <Your Dim > on 0, {<Your Measure>, Percent_of_All} on 1
from <Your Cueb>
NOTICE: replace the SUM function on the calculations if you need other aggregation.
I'm attempting to create a new Calculated Measure that is based on 2 different attributes. I can query the data directly to see that the values are there, but when I create the Calculated Member, it always returns null.
Here is what I have so far:
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS sum
(
Filter([Expense].MEMBERS, [Expense].[Amount Category] = "OS"
AND ([Expense].[Account Number] >= 51000
AND [Expense].[Account Number] < 52000))
,
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
Ultimately, I need to repeat this same pattern many times. A particular accounting "type" (Absorption, Selling & Marketing, Adminstrative, R&D, etc.) is based on a combination of the Category and a range of Account Numbers.
I've tried several combinations of Sum, Aggregate, Filter, IIF, etc. with no luck, the value is always null.
However, if I don't use Filter and just create a Tuple with 2 values, it does give me the data I'd expect, like this:
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS sum
(
{( [Expense].[Amount Category].&[OS], [Expense].[Account Number].&[51400] )}
,
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
But, I need to specify multiple account numbers, not just one.
In general, you should only use the FILTER function when you need to filter your fact table based on the value of some measure (for instance, all Sales Orders where Sales Amount > 10.000). It is not intended to filter members based on dimension properties (although it could probably work, but the performance would likely suffer).
If you want to filter by members of one or more dimension attributes, use tuples and sets to express the filtering:
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS
Sum(
{[Expense].[Account Number].&[51000]:[Expense].[Account Number].&[52000].lag(1)} *
[Expense].[Amount Category].&[OS],
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
Here, I've used the range operator : to construct a set consisting of all [Account Number] members greater than or equal to 51000 and less than 52000. I then cross-join * this set with the relevant [Amount Category] attribute, to get the relevant set of members that I want to sum my measure over.
Note that this only works if you actually have a member with the account number 51000 and 52000 in your Expense dimension (see comments).
An entirely different approach, would be to perform this logic in your ETL process. For example you could have a table of account-number ranges that map to a particular accounting type (Absorption, Selling & Marketing, etc.). You could then add a new attribute to your Expense-dimension, holding the accounting type for each account, and populate it using dynamic SQL and the aforementioned mapping table.
I don't go near cube scripts but do you not need to create some context via the currentmember function and also return some values for correct evaluation against the inequality operators (e.g.>) via the use of say the membervalue function ?
CREATE MEMBER CURRENTCUBE.[Measures].[Absorption]
AS sum
(
[Expense].[Amount Category].&[OS]
*
Filter(
[Expense].[Account Number].MEMBERS,
[Expense].[Account Number].currentmember.membervalue >= 51000
AND
[Expense].[Account Number].currentmember.membervalue < 52000
)
,
[Measures].[Amount - Expense]
),
VISIBLE = 1 , ASSOCIATED_MEASURE_GROUP = 'Expense';
EDIT
Dan has used the range operator :. Please make sure your hierarchy is ordered correctly and that the members you use with this operator actually exist. If they do not exist then they will be evaluated as null:
Against the AdvWks cube:
SELECT
{} ON 0
,{
[Date].[Calendar].[Month].&[2008]&[4]
:
[Date].[Calendar].[Month].&[2009]&[2]
} ON 1
FROM [Adventure Works];
Returns the following:
If the left hand member does not exist in the cube then it is evaluated as null and therefore open ended on that side:
SELECT
{} ON 0
,{
[Date].[Calendar].[Month].&[2008]&[4]
:
[Date].[Calendar].[Month].&[1066]&[2] //<<year 1066 obviously not in our cube
} ON 1
FROM [Adventure Works];
Returns:
I'm not very experienced in OLAP Cube + MDX, and I'm having a hard time trying to use twice the same measure in a cube.
Let's say that we have 3 Dimensions: D_DATE, D_USER, D_TYPE_OF_SALE_TARGET and 3 tables of Fact: F_SALE, F_MEETING, F_SALE_TARGET
F_SALE is linked to D_USER (who make the sale) and D_DATE (when)
F_SALE_TARGET is linked to D_USER, D_DATE, D_TYPE_OF_SALE_TARGET (meaning: user has to reach various goals/targets for a given month).
I can browse my cube:
Rows = Date * User
Cols = Number of sale, Total amount of sale + the value of 1 target (in the WHERE clause, I filter on [Dim TYPE SALE TARGET].[Code].&[code.numberOfSales])
How can I add other columns for other targets? As all the targets are in the same table, I don't see how to add a second measure from [Measures].[Value - F_SALE_TARGET] linked to a different code, ie. [Dim TYPE SALE TARGET].[Code].&[code.amountOfSale].
your question is not clear to me but it seems like one way to accomplish that is by creating Calculated Members. Basically, select you cube in BIDS, go to the Calculations tab and create Calculated Members. You would be able to insert your MDX query there. For each target type you can create a different calculation such as: ([Measures].[Value - F_SALE_TARGET], [Dim TYPE SALE TARGET].[Code].&[code.amountOfSale])
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)