I have a table as shown in the image. I need to create two filters in PowerPivot:
Group1Member_On_Any_Day: Set to 1 if any record in Group1MemberFlag is set to 1
Group1Member_On_All_Days: Set to 1 if all records in Group1MemberFlag is set to 1
The problems that I am running into are:
How do I filter on an aggregate
How do I ensure the aggregate filters are applied as I slice my
table by date or CustomerId
CustomerMembershipTable
I had a Eureka moment and realized that the filtering has to be done in the measure and that measure should be used to view the aggregations. For example, if I wanted to count customers who are a member of Group1, I would create a measure as follows:
Cnt_Customer_In_Group1:=Calculate(DISTINCTCOUNT([CustomerId]),FILTER('CustomerTable',[Group1MemberFlag]=1))
If you also have a measure that counts distinct CustomerIds, you can a filter on Group1MemberFlag to see which customerIds are in Group1 and which are not in Group1.
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 have one dimension that I want to put into filter, and created calculated member that should dynamically show number of selected members from the dimension.
The dimension does not have an All member.
So this is my attempt
with member [Measures].[Count1] as count(existing(([MyDimension].[MyDimensionHierarchy].members)))
select [Measures].[Count1] on 0
from [MyCube] -- gives me 1
and this one will give me 2 which is correct:
with member [Measures].[Count1] as count(existing(([MyDimension].[MyDimensionHierarchy].members)))
select [Measures].[Count1] on 0
from [MyCube]
where ({[MyDimension].[MyDimensionHierarchy].[Member1], [MyDimension].[MyDimensionHierarchy].[Member2]})
But, the problem is that when I create calculated member with the formula above, and drag Count1 to the Excel pivot table, and drag MyDimension as filter, and when I do multi-select of the dimension members, I want the count to dynamically change as I change number of members that are selected.
But Count1 always stays equal to 1.
In a meantime I have found an answer:
The query that I wrote in the question actually is not the query that Excel pivot table sends to the cube. Excel pivot table generates query like this:
SELECT FROM (SELECT ({[MyDimension].[MyDimensionHierarchy].[Member1],[MyDimension].[MyDimensionHierarchy].[Member2]}) ON COLUMNS
FROM [MyCube])
WHERE ([Measures].[Count1])
The way this should be done is by using dynamic set that contains filtered members:
create dynamic set [SelectedMembers] as existing( [MyDimension].[MyDimensionHierarchy].members )
And then:
create member Measures.SelectedMembersCount as count([SelectedMembers])
So this set dynamically changes as different members are selected in the filter and SelectedMembersCount is dynamically changed along the way.
Am trying to rank groups by summing a field (not a calculated column) for each group so I get a static answer for each row in my table.
For example, I may have a table with state, agent, and sales. Sales is a field, not a measure. There can be many agents within a state, so there are many rows for each individual state. I am trying to rank the states by total sales within each state.
I have tried many things, but the ones that make the most sense to me are:
rankx(CALCULATETABLE(Table,allexcept(Table,Table[AGENT]),sum([Sales]),,DESC)
and
=rankx(SUMMARIZE(State,Table[State],"Sales",sum(Table[Sales])),[Sales])
The first one is creating a table where it sums sales without grouping by Agent. and then tries to rank based on that. I get #ERROR on this one.
The second one creates a table using SUMMARIZE with only sum of Sales grouped by state, then tries to take that table and rank the states based on Sales. For this one I get a rank of 1 for every row.
I think, but am not sure, that my problem is coming from the sales being a static field and not a calculated measure. I can't figure out where to go from here. Any help?
Assuming your data looks something like this...
...have you tried this:
Ranking Measure = RANKX(ALL('Table'[STATE]),CALCULATE(SUM('Table'[Sales])))
The ALL('Table'[STATE]) says to rank all states. The CALCULATE(SUM('Table'[Sales])) says to rank by the sum of their sales. The CALCULATE wrapper is important; a plain SUM('Table'[Sales]) will be filtered to the current row context, resulting in every state being ranked #1. (Alternatively, you can spin off SUM('Table'[Sales]) into a separate Sales measure - which I'd recommend.)
Note: the ranks will change based on slicers/filters (e.g. a filter by agent will re-rank the states by that agent). If you're looking for a static rank of states by their total sales (i.e. not affected by filters on agent and always looking at the entire table), then try this:
Static Ranking Measure = CALCULATE([Ranking Measure], ALLEXCEPT('Table', 'Table'[State]))
This takes the same ranking measure, but removes all filters except the state filter (which you need to leave, as that's the column you're ranking by).
I did figure out a solution that's pretty simple, but it's messier than I'd like. If it's the only thing that works though, that's okay.
I created a new table with each distinct state along with a sum of sales then just do a basic RANKX on that table.
Using SSRS 2010
I have Two groups YearMonth and Insured. I need to display only 50 records per page based on a group "Insured". So I have created parent group "GroupPageBreakOnly" and used this expression =CEILING(RowNumber(Nothing)/50).
I ensured that the Page Break at end is checked so that individual groups appear in individual page.
As a result the first page displays 31 rows, the second one 50 rows, and the third one 9 rows.
I tried to specify data region "Insured"
=CEILING(RowNumber("Insured")/50),
but it gives me an error:
...the value of the scope parameter of RowNumber must equal the name of the group directly containing the current group.
What am I missing here?
Unless you need this report to do other things, I would apply the grouping and aggregation in the Dataset itself which is generally a lot more efficient anyway.
Have you tried using ROW_NUMBER() OVER (PARTITION BY YearMonth, Insured ORDER BY YearMonth, Insured) to give the number of rows, perhaps even throwing in a % 50 at the end to see which group of 50 it fell into?
This can then be grouped on in your report.
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)