I am trying to sum every line in a table summarizing it by two fields in webi.
I have a table with the following columns:
Risk, Year, AssessedBy, Weight, Value.
I have filtered the table by Year = 2018 and Risk = "01". Thus, I only have the info for that year and that risk.
Each person assessing has a different weight in the final valuation by risk and year. What I have done is divide the assessing person's weight by the total sum of every Weight in the table [ sum(weight) in block ].
The problem is that when I delete the filter, the in block clause makes that the total sum of the weights changes to the total sum of the weights for every year in the table.
I would need something to calculate the total sum for each year and risk.
Just solved it! Just see Sumal Kunir answer: http://www.forumtopics.com/busobj/viewtopic.php?p=971131
=sum([Var_a] for each(Dimension;dimension)) In (Demension)
where var_a is the measure, foreach defines a background to base in and in defines the level at which you want to aggregate.
Related
I am currently attempting to use DAX queries to calculate the proportion of the balance attributed to each State in my analysis cube, from the following image:
I currently have a Sales table with a ReportDateKey that joins a ReportDate table that has a DateKey
If I use the following statement:
AllCurrentBalanceByDate:=CALCULATE([TotalCurrentBalance],ALLSELECTED())
It gives me the overall total, ignoring the date altogether, which is a useless figure.
If I enter the following query and display it in the excel spreadsheet:
AllCurrentBalanceByDate:=CALCULATE([TotalCurrentBalance],ALLSELECTED('Report Date'[Month]))
it is returning the same data as found in the Balance column. Again, useless. I need a total for each month, so that I can calculate the state balance / overall total for that month to get the proportion/percentage attributable to that State.
What am I doing wrong?
So if you want your measure to ignore whichever State is selected, you need to include the State columns in your ALL filter.
Also I suppose you want to use ALL instead of ALLSELECTED as your overall balance per month shouldn't be affected by external filters on state (but this depends on your use case)?
AllCurrentBalanceByDate:=CALCULATE(SUM([CurrentBalance]),ALL(Geography[StateName]))
I have a multidimensional cube that needs a custom measure that I'm not sure how to build.
That data looks like this:
MemberID-----Date-------EventType
1--------------1/1/2016-------1
2--------------1/1/2016-------2
3--------------2/1/2016-------1
2--------------2/1/2016-------2
4--------------2/1/2016-------2
There is a count measure in the cube, but others can be added if needed. I need to create a measure that will use whatever filters the user applies and then count the EventType (1 and 2 only) by month, divide the resulting counts for EventType 1 into the count for EventType 2 (for each month individually), and finally sum the monthly results. For example 1/1/2016 would be 1/1=1 (count of EventType 1 and count of EventType 2) and 2/1/2016 would be 1/2=0.5 so the resulting measure value for the two months would be 1+0.5=1.5. Any help is greatly appreciated.
Let's assume you have a Date dimension with an attribute called Month. And let's assume you have an EventType dimension. And let's assume you have a count measure in your measure group called Cnt. Here's what else you need to do.
First, go to the DSV and add a new calculated column to the fact table which is called NullInt and is the following expression:
cast(null as int)
Then create a new Sum measure in your measure group off that column and call the measure My Rollup. Under the Source property, change NullHandling to Preserve so that it will start off null.
To explain why we're doing this, a scoped assignment to a physical measure will aggregate up. (If you assign a value to a physical measure at the grain of each month, then it will rollup to the grand total.) But a scoped assignment to a calculated measure doesn't roll up.
Then in your MDX script add the following calculations:
scope([Date].[Month].[Month].Members); //calculate at the month level then rollup
[Measures].[My Rollup] = DIVIDE(
([Event Type].[Event Type].&[1],[Measures].[Cnt]),
([Event Type].[Event Type].&[2],[Measures].[Cnt])
);
end scope;
Note that your version of SSAS probably has the DIVIDE function if it's AS2012 with the latest service pack or newer. But if it doesn't, you can always do division the old fashioned way as IIF(denom=0,null,num/denom).
I am a graduate intern at a big company and I'm having some trouble with creating a measure in PowerPivot.
I'm quite new with PowerPivot and I need some help. I am the first person to use PowerPivot in this office so I can't ask for help here.
I have a fact table that has basically all journal entries. See next table. All entries are done with a unique ID (serialnumber) for every product
ID DATE ACCOUNT# AMOUNT
110 2010-1-1 900 $1000
There is a dimension table with has all accounts allocated to a specific country and expense or revenue.
ACCOUNT# Expense Country
900 Revenue Germany
And another dimension table to split the dates.
The third dimension table contains product information, but also contains a column with a certain expense (Expense X).
ID Expense X ProductName Productcolour
110 $50 Flower Green
I made sure I made the correct relations between the tables of course. And slicing works in general.
To calculate the margin I need to deduct this expense x from the revenue. I already made a measure that shows total Revenue, that one was easy.
Now I need a measure to show the total for Expense X, related to productID. So I can slice in a pivot table on date and product name etc.
The problem is that I can't use RELATED function because the serial number is used multiple times in the fact table (journal entries can have the same serial number)
And if I use the SUM or CALCULATE function it won't slice properly.
So how can I calculate the total for expense X so it will slice properly?
Check the function RELATEDTABLE.
If you create a dummy dataset I can play around and send you a solution.
This is a slight modification of what I stumbled upon while searching the web:
Let's say I have a dimension PROJECTS which contains:
project_id - unique id
category - category of a cost
project_date - date of summing up the cost
My warehouse also has the dimension of TIME with date, and a dimension COSTS containing values of costs. Those three dimensions are connected by the measure group EXPENSES which has:
id_date
id_cost
id_project
I want to wirte an MDX query which would group the projects by their category, and sum up all the costs, but only those which do not exceed the date given in the project_date attribute of the dimension PROJECTS (each category has the same project_date, I know it's redundant but I can't change it..)
I'm not sure, but maybe something alongside this?
SELECT
[COSTS].[COST] ON 0,
[PROJECTS].[category] ON 1
FROM [CUBE]
WHERE
[PROJECTS].[project_date] < #project_date
I have cost center allocation data that is currently fully populated, one record per day, each with one cost center dimension key. The cube has a head count measure (the data is set to "1"), and the aggregate function is set to "LastChild". This means that a head count report will count a person only once in a cost center in any given time period.
Introducing partial allocations - a new measure will have a percentage value for the allocation, allowing for multiple concurrent cost centers where the allocation should add up to 100% (with "day" being the granular level). I am trying to figure out how to configure the aggregation over other time periods. I thought that "Average" should work just fine, i.e. a person who is allocated to a cost center at 50% for half the time period will be reported at 25% for that period.
The problem that I see is that my facts are not populated for days where the allocation to a cost center was 0%. To illustrate:
Employee1 CostCenterA 1/1/2013 50%
Employee1 CostCenterB 1/1/2013 50%
Employee1 CostCenterA 1/2/2013 100%
Employee1 CostCenterA 1/3/2013 100%
... etc with 100% in CostCenterA for all days
The above data on a report by month shows 50% for the allocation to CostCenterB, even though the person was only allocated for one day, and the average percentage on a monthly basis should be 1.6%.
I suppose I could generate the 0%-allocations in the data, but my fact table would explode as a result, so I'd much rather change how the "average" aggregation treats percentage values in facts that are sparsely populated, i.e. the average should be calculated based on the number of granular units in the reporting period (days in the month, in this case 0.5/31), not the number of rows in the fact table (0.5/1). Can this be done in SSAS?
If the measure with the average allocation is off by a factor that is proportional to the "sparseness" of my facts, i.e. the ratio of days in a period and actual fact rows, then it can be corrected as follows:
adjusted average allocation =
(calculated average allocation) * (fact count)/(number of days in period)
I created two new hidden measures, one named [Fact Count] for the fact count (a measure using the AggregateFunction "Count") and a calculated measure named [Days In Period Count] for the number of days, using the expression
COUNT(Descendants([Date].[Calendar].CurrentMember,5),INCLUDEEMPTY)
with [Calendar] being the name of the hierarchy in my Date dimension.
Finally, I added a calculated measure that implements the corrective formula:
[Measures].[Allocative Head Count]/
(
[Measures].[Days In Period Count]/[Measures].[Fact Count]
)
and named it [Adjusted Average Allocation]. This I can now use in reports and it appears to somewhat approximate the average cost center allocation over longer periods.
The formular for [Days In Period Count] btw does not work for the row totals when filters are involved. I opened another question for this.