Finding 2nd maximum in crosstab of Cognos Anlytics - max

I am using Cognos Analytic v11 (with a dimensional DB).
I have a table showing the 24-hour readings of sensor A, B and C. Finding the maximum in crosstab is easy using the Summarize function; but how do I find the 2nd maximum (i.e 2nd highest)?

I was able to get this to work for me:
aggregate([{Amount Field}] within set subset(order([{Sensor Field}],[{Amount Field}],DESC),1,1))
Replace {Amount Field} with the name of the actual amount data item and {Sensor Field} with the item you want to find the 2nd maximum within.
The order function sorts the set by the amount field. The first member of the resulting set is the maximum. The second member of the resulting set is the 2nd maximum. We isolate the second maximum by using the subset function to get the member with index 1 and then we aggregate the measure for this one member.

Related

Dynamic Calculated Column on different report level SSAS DAX query

I'm trying to create a calculated column based on a derived measure in SSAS cube, this measure which will count the number of cases per order so for one order if it has 3 cases it will have the value 3.
Now I'm trying to create a bucket attribute which says 1caseOrder,2caseOrder,3caseOrder,3+caseOrder. I tried the below one
IF([nrofcase] = 1, "nrofcase[1]", IF([nrofcase] = 2, "nrofcase[2]",
IF([nrofcase] = 3, "nrofcase[3]", "nrofcase[>3]") )
But it doesn't work as expected, when the level of the report is changed from qtr to week it was suppose to recalculate on different level.
Please let me know if it case work.
Calculated columns are static. When the column is added and when the table is processed, the value is calculated and stored. The only way for the value to change is to reprocess the model. If the formula refers to a DAX measure, it will use the measure without any of the context from the report (eg. no row filters or slicers, etc.).
Think of it this way:
Calculated column is a fact about a row that doesn't change. It is known just by looking at a single row. An example of this is Cost = [Quantity] * [Unit Price]. Cost never changes and is known by looking at the Quantity and Unit Price columns. It doesn't matter what filters or context are in the report. Cost doesn't change.
A measure is a fact about a table. You have to look at multiple rows to calculate its value. An example is Total Cost = SUM(Sales[Cost]). You want this value to change depending on the context of time, region, product, etc., so it's value is not stored but calculated dynamically in the report.
It sounds like for your data, there are multiple rows that tell you the number of cases per order, so this is a measure. Use a measure instead of a calculated column.

Is there any option to do FOR loop in excel?

I have an excel that I'm calculating my Scrum Task's completed average. I have Story point item also in the excel. My calculation is:
Result= SP * percentage of completion --> This calculation is for each row and after that I sum up all result and taking the summary.
But sometimes I am adding new task and for each task I am adding the calculation to the average result.
Is there any way to use for loop in the excel?
for(int i=0;i<50;i++){ if(SP!=null && task!=null)(B+i)*(L+i)}
My calculation is like below:
AVERAGE((B4*L4+B5*L5+B6*L6+B7*L7+B8*L8+B9*L9+B10*L10)/SUM(B4:B10))
First of all, AVERAGE is not doing anything in your formula, since the argument you pass to it is just one single value. You already do an average calculation by dividing by the sum. That average is in fact a weighted average, and so you could not even achieve that with a plain AVERAGE function.
I see several ways to make this formula more generic, so it keeps working when you add rows:
1. Use SUMPRODUCT
=SUMPRODUCT(B4:B100,L4:L100)/SUM(B4:B100)
The row number 100 is chosen arbitrarily, but should evidently encompass all data rows. If you have no data occurring below your table, then it is safe to add a large margin. You'll want to avoid the situation where you think you add a line to the table, but actually get outside of the range of the formula. Using proper Excel tables can help to avoid this situation.
2. Use an array formula
This would be a second resort for when the formula becomes more complicated and cannot be executed with a "simple" SUMPRODUCT. But the above would translate to this array formula:
=SUM(B4:B100*L4:L100)/SUM(B4:B100)
Once you have typed this in the formula bar, make sure to press Ctrl+Shift+Enter to enter it. Only then will it act as an array formula.
Again, the same remark about row number 100.
3. Use an extra column
Things get easy when you use an extra column for storing the product of B & L values for each row. So you would put in cell N4 the following formula:
=B4*L4
...and then copy that relative formula to the other rows. You can hide that column if you want.
Then the overal formula can be:
=SUM(N4:N100)/SUM(B4:B100)
With this solution you must take care to always copy a row when inserting a new row, as you need the N column to have the intermediate product formula also for any new row.

How to summarize by calculated measure in Power BI?

I have transactional data which contains customer information as well as stores they shopped from. I can count the number of different stores each customer used by a simple DISTINCTCOUNT([Site Name]) measure.
There are millions of customers and I want to make a simple summary table which shows the sum of # customers who visited X number of stores. Like a histogram. Maximum stores they visited is 6, minimum is 1.
I know there are multiple ways to do this but I am new to DAX and can't do what I think yet.
The easiest way:
Assuming your DISTINCTCOUNT([Site Name]) measure is called CustomerStoreCount ...
Add a new dimension table, StoreCount, to your model containing a single column, StoreCount. Populate it with the values 1,2,3,4,5,6 (... up to maximum number of stores.)
Create a measure, ThisStoreCount = MAX(StoreCount[StoreCount]).
Create a base customer count measure, TotalCustomers:=DISTINCTCOUNT(CustomerTable[Customer])
Create a contextual measure, CustomersWhoVisitedXNumberOfStores := CALCULATE ( TotalCustomers, FILTER(VALUES(CustomerTable[Customer]), ThisStoreCount = CustomerStoreCount) )
On your pivot table / reporting tool, etc. use StoreCount[StoreCount] on the axes and CustomersWhOVisitedXNumberOfStores as the measure.
So basically walk through the customer list (since there's no relationship between StoreCount and CustomerTable), compare that customer's CustomerStoreCount with the maximum StoreCount[StoreCount] value, which for each StoreCount[StoreCount] value is ... drum roll itself. If it matches, keep it, otherwise filter it out; you end up with a count of customers whose store visits equals the value of StoreCount[StoreCount].
And of course the more general modeling hint: when you want to display a metric by something (i.e. customer count by number of stores visited), that something is an attribute, not a metric.

Tableau - Calculated fields / grouping / Custom Dim

Tableau:
This may seem simple, but I ran out of the usual tricks I've used in other systems.
I want a variance column. Essentially adding a member 'Variance' to the Act/Plan dimension which only contains the members 'Actual' and 'Plan'
I've come in where the data structure and reporting is set up like so:
Actual | Plan
Profit measure
measure 2
measure 3
etc
The goal is to have a Variance column (calculated and not part of the Actual/Plan dimension)
Actual | Plan | Variance
Profit measure
measure 2
measure 3
etc
There are solutions where it works for one measure only, and I've looked into that.
ie, create calculated field as such
Profit_Actual | Profit_Plan | Variance
You put this on the columns, and you get a grid that I want... except a grid with only 1 measure.
This does not work if I want to run several measures on rows. Essentially the solution above will only display the Profit measure, not Measure 1_Actual , Measure 2_Plan etc.
So I tried a trick where I grouped a the 3 calculated measures, ie Profit_Actual | Profit_Plan | Profit_Variance as 'Profit_Measure'
Created a parameter list - 'Actual', 'Plan', 'Variance'
Now I can half achieve my goal, by having the parameter on columns and the 'Profit Measure' on Rows (so I can have Measure 123_group etc down on rows too). Trouble is, I found that parameters are single select only. Only if it can display all options in the custom paramater at once, I would've solved my problem.
Any ideas on how I can achieve the Variance column I want?
Virtually adding a member to a dimension/Calculated fieds/tricks/workaround
Thank you
Any leads is appreciated
Gemmo
Okay. First thing, I had a really hard time trying to understand how your data is organized, try to be more clear (say how each entry in your database looks like, and not how a specific view in Tableau looks like).
But I think I got it. I guess you have a collection of entries, and each entry has a number of measure fields (profits and etc.) and an Act/Plan field, to identify whether that entry is an actual value or a planned value. Is that correct?
Well, if that's the case, I'm sorry to say you have to calculate a variance field for each dimension. Think about it, how your original dataset is structured. Do you think you can add a single field "Variance" to represent the variance of each measure? Well, you can, store the values in a string, and then collect it back using some string functions, but it's not very practical. The problem is that each entry have many measures, if it had only 1 measure, than 1 single variance field would suffice.
So, if you can re-organize your data, what would be an easier to work set (but with many more entries) is something with the fields: Measure, Value, Actual/Plan. The measure field would have a string to identify what you're measuring in that entry. Value would be a number to represent the actual measure. And the Actual/Plan is the same. For instance:
Measure Value Actual/Plan
Profit 100 Actual
So, each line in your current model would become n entries, where n is the number of measures you have right now. So a larger dataset in a way, but easier to work with. Think about, now you can have a calculated field, and use some table calculations to calculate the variance only for that measure and/or Actual/Plan. Just use WINDOW_VAR, and put Measure and/or Actual/Plan in the partition.
Table calculations are awesome, take a look at this to understand it better. http://onlinehelp.tableausoftware.com/current/pro/online/en-us/help.htm#calculations_tablecalculations_understanding_addressing.html
I generally like to have my data staged such that Actual is its own column and Plan is its own column in the data being fed to Tableau. It makes calculations so much easier.
If your data is such that there is a column called "Actual/Plan" and every row is populated with either "Actual" or "Plan" and there is another column called "Value" or "Measure" that is populated with the values, you can force Tableau to make them columns assuming you can't or won't rearrange your data.
Create a calculated field called "Actual" with the following calc:
IF [Actual/Plan] = 'Actual' THEN [Value] END
Similarly, create a calculated field called "Plan" with the following calc:
IF [Actual/Plan] = 'Plan' THEN [Value] END
Now, you can finally create your "Variance" and "Variance %" calculations (respectively):
SUM([Actual]) - SUM([Plan])
[Variance] / SUM([Plan])

MDX: Filtering a member set by a measure's table values

I have some numbers in a fact table, and have generated a measure which use the SUM aggregator to summarize the numbers. But the problem is that I only want to sum the numbers that are higher than, say 10. I tried using a generic expression in the measure definition, and that works of course, but the problem is that I need to be able to dynamically set that value, because it's not always 10, meaning users should be able to select it themselves.
More specifically, my current MDX looks like this:
WITH
SET [Email Measures] AS '{[Measures].[Number Of Answered Cases],
[Measures].[Max Expedition Time First In Case], [Measures].[Avg Expedition Times First In Case],
[Measures].[Number Of Incoming Email Requests], [Measures].[Avg Number Of Emails In Cases],
[Measures].[Avg Expedition Times Total],[Measures].[Number Of Answered Incoming Emails]}'
SET [Organizations] AS '{[Organization.Id].[860]}'
SET [Operators] AS '{[Operator.Id].[3379],[Operator.Id].[3181]}'
SET [Email Accounts] AS '{[Email Account.Id].[6]}'
MEMBER [Time.Date].[Date Period] AS Aggregate ({[Time.Date].[2008].[11].[11] :[Time.Date].[2009].[1].[2] })
MEMBER [Email.Type].[Email Types] AS Aggregate ({[Email.Type].[0]})
SELECT {[Email Measures]} ON columns,
[Operators] ON rows
FROM [Email_Fact]
WHERE ( [Time.Date].[Date Period] )
Now, the member in question is the calculated member [Avg Expedition Times Total]. This member takes in two measures; [Sum Expedition Times] and [Nr of Expedition Times] and splits one on the other to get the average, all this presently works. However, I want [Sum Expedition Times] to only summarize values over or under a parameter of my/the user's wish.
How do I filter the numbers [Sum Expedition Times] iterates through, rather than filtering on the sum that the measure gives me in the end?
You could move the member into the MDX query, instead of putting it in the cube. Then you get something like....
WITH
MEMBER [Avg Expedition Times Total] AS
SUM(
FILTER([Your Dimension],
[Measure you want to filter] > 10),
[Measure you want to sum])
I'm not sure exactly which dimensions and measure you want to filter and sum by, but I think this is a step in the right direction. If your users can't modify the MDX (or don't want to!) then creating multiple measures is a pretty solid solution too.
You need to have a Dimension which has distinct values of this Measure( Incase if the number of distinct values is too high then perhaps some sort of range). Then you join this dimension to the fact. The joining should be simple. The Measure column will become the key column also. Now you just need to refer dimension memeber.

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