In my product dimension, I have an attribute called CustomerRating which is a string. Possible values are "1", "2", "3", and "4".
I want to turn this attribute into a Measure that averages ratings for collections of products.
with member [Measures].[Product Rating] as
( [Product].[Project Name].CurrentMember.Properties("CustomerRating"))
select [Measures].[Product Rating] on columns
from [MyCube]
This query produces an error - I suspect because I'm dealing with a string.
How do I turn customer rating into a measure that is an average rather than a sum?
The best approach would be to add an int column to the source table of the dimension, maybe just as a named calculation in the DSV. Then you would add a measure group on the dimension table, and define a measure rating_sum that sums this column, and a count measure in this measure group.
Then define a calculated measure as rating_sum / count.
If everything works, make the two measures rating_sum and count invisible.
Not tested but I'm wondering if this errors?
WITH
MEMBER [Measures].[Product Rating] AS
CInt([Product].[Project Name].CurrentMember.Properties("CustomerRating"))
SELECT
{[Measures].[Product Rating]} ON COLUMNS
From [MyCube]
Related
I have a multi-dimensional cube that has multiple rows for each shop. There is a ShopCount measure that is a DistinctCount over the ShopKey field in the cube, which is in another measure group. I can get Shop counts over all sorts of different dimensions, which in this case is usually location. That works fine.
Now I want a variant of this. I want an inline distinct count of shops based on another measure or dimension.
Here is an example mdx that gives me a distinct count of shops for a particular month, where the shop type is either automotive or camping.
SELECT [Measures].[Shop Count] ON COLUMNS
FROM [Retail Cube]
WHERE ([Report Date].[Month].[201905],
{[Shop].[ShopType].&[Automotive],[Shop].[ShopType].&[Camping]})
CELL PROPERTIES VALUE
In Excel, I would like to be able to get another column that has the distinct count of Automotive and Camping shops over the range of months in my database. I would like to then be able to filter the columns by all the existing dimensions that I am currently filtering by.
I tried creating a calculated field in the Calculations tab, such as:
COUNT(DISTINCT CASE WHEN [Shop].[ShopType].&[Automotive] THEN [Shop].[Shop Key]
WHEN [Shop].[ShopType].&[Camping] THEN [Shop].[Shop Key]
ELSE NULL END)
(Note: Shop Key is what I do my Distinct Count over)
After substantial processing it came up with an error in that column.
How can I achieve what I am trying to do?
I am trying to calculate percentile (for example 90th percentile point of my measure) in a cube and I think I am almost there. The problem I am facing is, I am able to return the row number of the 90th percentile, but do not know how to get my measure.
With
Member [Measures].[cnt] as
Count(NonEmpty(
-- dimensions to find percentile on (the same should be repeated again
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members
,
-- add the measure to group
[Measures].[Profit]))
-- define percentile
Member [Measures].[Percentile] as 90
Member [Measures].[PercentileInt] as Int((([Measures].[cnt]) * [Measures].[Percentile]) / 100)
**-- this part finds the tuple from the set based on the index of the percentile point and I am using the item(index) to get the necessary info from tuple and I am unable to get the measure part
Member [Measures].[PercentileLo] as
(
Order(
NonEmpty(
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members,
[Measures].[Profit]),
[Measures].[Profit].Value, BDESC)).Item([Measures].[PercentileInt]).Item(3)**
select
{
[Measures].[cnt],
[Measures].[Percentile],[Measures].[PercentileInt],
[Measures].[PercentileLo],
[Measures].[Profit]
}
on 0
from
[TestData]
I think there must a way to get measure of a tuple found through index of a set. Please help, let me know if you need any more information. Thanks!
You should extract the tuple at position [Measures].[PercentileInt] from your set and add the measure to it to build a tuple of four elements. Then you want to return its value as the measure PercentileLo, i. e. define
Member [Measures].[PercentileLo] as
(
[Measures].[Profit],
Order(
NonEmpty(
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members,
[Measures].[Profit]),
[Measures].[Profit], BDESC)).Item([Measures].[PercentileInt])
)
The way you implemented it, you tried to extract the fourth (as Item() starts counting from zero) item from a tuple containing only three elements. Your ordered set only has three hierarchies.
Just another unrelated remark: I think you should avoid using complete hierarchies for [Calendar].[Hierarchy].members, [Region Dim].[Region].members, and [Product Dim].[Product].members. Your code looks like you are including all levels (including the all member) in the calculation. But I do not know the structure and names of your cube, hence I may be wrong with this.
An alternate method could be to find the median of the last 20% of the records in the table. I've used this combination of functions to find the 75th percentile. By dividing the record count by 5, you can use the TopCount function to return a set of tuples that make up 20% of the whole table sorted in descending order by your target measure. The median function should then land you at the correct 90th percentile value without having to find the record's coordinates. In my own use, I use the same measure for the last parameter in both the Median and TopCount functions.
Here's my code:
WITH MEMBER Measures.[90th Percentile] AS MEDIAN(
TOPCOUNT(
[set definition]
,Measures.[Fact Table Record Count] / 5
,Measures.[Value by which to sort the set so the first 20% of records are chosen]
)
,Measures.[Value from which the median should be determined]
)
Based on what you've supplied in your problem definition, I would expect your code to look something like this:
WITH MEMBER Measures.[90th Percentile] AS MEDIAN(
TOPCOUNT(
{
[Calendar].[Hierarchy].members *
[Region Dim].[Region].members *
[Product Dim].[Product].members
}
,Measures.[Fact Table Record Count] / 5
,[Measures].[Profit]
)
,[Measures].[Profit]
)
I am new to MDX expressions and I am trying to create one that sums the value of a given measure filtered by dimensions.
In my database I have several different dimensions that have the same name: "Answer". To sum them up, I have created the query below:
WITH MEMBER Measures.Total as SUM ({[Activity].[Activity].&[14], [Activity][Activity].&[22]},
[Measures].[Activity time])
SELECT NON EMPTY [Measures].[Total] on COLUMNS from [My Analytics]
This query works, however I had to use the "&[14]" and "&[22]" statments that correspond to two different "Answer" dimensions.
Since I have more than two dimensions with the same name, is there a way to rewrite the query above in a way that I would select all these dimensions without having to add their unique ID? For example, I would re-write the query as something like this:
WITH MEMBER Measures.Total as SUM ({[Activity].[Activity].&["Answer"]},
[Measures].[Activity time])
SELECT NON EMPTY [Measures].[Total] on COLUMNS from [My Analytics]
Is this possible?
Thanks!
You can use the Filter function as following:
with
set [my-answers] as
Filter( [Activity].[Activity].members,
[Activity].[Activity].currentMember.name = 'Answer'
)
member [Measures].[Total] as Sum( [my-answers] )
...
Being an SSAS newbie, I was wondering if it's possible to create a calculated member that references an individual row's value as well as the aggregated value in order to create a percentage?
For example, if I have a fact table with ValueA, I'd like to create a calculate member that essentially performed:
[Measures].[ValueA] (for each row I've sliced the data by) / [Measures].[ValueA] (the total)
Also I'd like to keep the total as the sum of whatever's been filtered in the cube browser. I feel certain this must be possible but I'm clearly missing something.
You can use the Axis function. Her is an example:
WITH MEMBER [Measures].[Percentage] AS
[Measures].[ValueA] / (Axis(1).CurrenMember.Parent, [Measures].[ValueA])
SELECT {[Measures].[ValueA], [Measures].[Percentage]} ON 0,
'what you want' ON 1
FROM your cube
(You may need to add check in the calculated member expression)
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)