DAX Running Running Total Based on None Date Columns - dax

I need to do a running total and filter by two none date fields.
All data is in a single table that is used to house Cycle Times for Part Numbers at each of their respective steps. This table contains a record for each combination of Step and Part. I need to get a running total for Cycle Times on all complete and current steps.
For example in the Table View, if you were to go to CycleHoursComplete at StepNo 40 I need it to = 2.86 or the sum of StepCycleHours with StepNo's <= the StepNo for the given record.
Currently "CycleHoursComplete" = CALCULATE( SUM ( Routing[StepCycleHours] ) , GROUPBY(Routing, Routing[PartNo]), (Routing[StepNo] <= Routing[StepNo] )), and that is not working.

You can easily do running totals with non-date fields as long as you have a numerical identifier to sort by, such as an ID column or in your case, the StepNo column.
You just need to use a combination of FILTER and EARLIER functions. Here's the DAX:
=CALCULATE(SUM([StepCycleHours]),ALL(Cycle),Cycle[StepNo]<=EARLIER(Cycle[StepNo]))
Note my table is called "Cycle"- you would need to replace that with your table name (Routing).
I noticed you tried to use a similar logic as the one I pasted above in the formula, but you forgot to use EARLIER, which is crucial to create row-level context.
Result:

Related

Compare Dynamic Lists Power BI

I have a table ("Issues") which I am creating in PowerBI from a JIRA data connector, so this changes each time I refresh it. I have three columns I am using
Form Name
Effort
Status
I created a second table and have summarized the Form Names and obtained the Total Effort:
SUMMARIZE(Issues,Issues[Form Name],"Total Effort",SUM(Issues[Effort (Days)]))
But I also want to add in a column for
Total Effort for each form name where the Status field is "Done"
My issue is that I don't know how to compare both tables / form names since these might change each time I refresh the table.
I need to write a conditional, something like
For each form name, print the total effort for each form name, print the total effort for each form name where the status is done
I have tried SUMX, CALCULATE, SUM, FILTER but cannot get these to work - can someone help, please?
If all you need is to add a column to your summarized table that sums "Effort" only when the Status is set to 'Done' -- then this is the right place to use CALCULATE.
Table =
SUMMARIZE(
Issues,
Issues[Form Name],
"Total Effort", SUM(Issues[Effort]),
"Total Effort (Done)", CALCULATE(SUM(Issues[Effort]), Issues[Status] = "Done")
)
Here is a quick capture of what some of the mock data that I used to test this looks like. The Matrix is just the mock data with [Form Name] on the rows and [Status] on the columns. The last table shows the 'summarized' data calculated by the DAX above. You can compare this to the values in the matrix and see that they tie out.

How to create a DAX cross-sectional measure?

I don't know if I even worded the question correctly, but I'm trying to create a measure that depends on what is showing in the pivot table (using PowerPivot). In the image I posted, "DealMonth" is an expression in the PowerQuery table itself that simply takes the start date of the employee and subtracts it from the month a deal was closed in. That will show how long it took for that salesperson to close the deal. "TenureMonths" is also an expression in the PowerQuery table that calculates the tenure of the person. The values populating this screenshot are coming from a total headcount measure created. What I'm trying to do is create a separate measure that will show when the "TenureMonths" is less than the "DealMonth." So if the TenureMonths is 5, then after DealMonth of 5, the value would be 0. Is this possible?
Screenshot
I should add the following information.
"DealMonth" - Comes from the FactData table
"TenureMonths" - Comes from the DimSalesStart table
These two tables are joined by name. I feel like I'm so close because I can see what I want. The second image below is a copy/paste of the pivot table result but with my edits to show what I'd want to have shown. Basically, if(TenureMonths >= DealMonth,1,0). The trouble seems to be that since they're in two different tables, I can't make it work. The rows in the fact table are transactions, but the rows in the dim table are just the people with their start and end dates.
Desired Result
This is possible with some IF([measure1]<[measure2],blank(),[measure1]), however without seeing more of the data it will be hard to guide you specifically.
However you need to create two separate measures, one for TenureMonths and one for DealMonth, depending on the data this can be done with an aggregator forumla such as sum, min, max, etc (depends if there will be more than one value).
Then reference those two measures in the formula pattern I mentioned above, and that should give you want you want.
I figured out a solution. I added a dimension table for DealMonth itself and joined to my fact table. That allowed me to do the formulas that I needed.

How to get the sum of values of a column in tmap?

I have 2 columns - Matches(Integer), Accounts_type(String). And i want to create a third column where i want to get proportions of matches played by different account types. I am new to Talend & am facing issue with this for past 2 days & did a lot of research but to no avail. Please help..
You can do it like this:
You need to read your source data twice (I used tFixedFlowInput_1 and tFixedFlowInput_2 with the same data). The idea is to calculate the total of your matches in tAggregateRow_1, it simply does a sum of all Matches without a group by column, then use that as a lookup.
The tMap then joins your source data with the calculated total. Since the total will always be one record, you don't need any join column. You then simply divide Matches by Total as required.
This is supposing you have unique values in Account_type; if you don't, you need to add another tAggregateRow between your source and tMap_1, in order to get sum of Matches for each Account_type (group by Account_type).

Column not defined in current context

I'm trying something very simple in DAX:
[Balance] := 'Inventory'[Inventory Amount]*10
I get a "column does not exist in current context" error. What does this mean?
You are getting this error because it was expecting an aggregate. You are creating a calculated measure but referring to a row and it doesn't have context for this row. I'm not sure what you are trying to achieve. If you need to calculate things on a row level, you'll need to use a SUMX (or you need to create a calculated column that multiplies the Inventory Amount column by 10 and then SUM it. Otherwise, you can use SUM with just one calc.
If you just need to add all the inventory amounts on every row in the query context and then multiply by 10, you can do
Balance:= SUM('Inventory'[Inventory Amount])
If the number you multiple will not always be 10, I suggest putting that formula in a separate calculated column (let's call it 'Inventory[Factor]. Then create a calculation like:
Balance:= SUMX('Inventory', 'Inventory'[Inventory Amount] * 'Inventory'[Factor])
The difference between these two is that the SUM will do the aggregation first. The SUMX will do the row-level calculation first and then aggregate. Since I don't know what you are trying to do, I gave you both options. SUMX will probably be slower, so you probably want to avoid that.
Here is a relevant blog post on the subject. In general check out PowerPivotPro.com and DaxPatterns.com when trying to find your way through DAX.

Can I compare values in the same column in adjacent rows in PowerPivot?

I have a PowerPivot table for which I need to be able to determine how long an item was in an Error state. My data set looks something like this:
What I need to be able to do is to look at the values in the ID and State columns, and see if the value in the previous row is ERROR in the State column, and the same in the ID column. If it is, I then need to calculate the difference between the Changed Date values in those two rows.
So, for example, when I got to row 4, I would see that the value in the State column for Row 3, the previous row, is ERROR, and that the value in the ID column in the previous row is the same as the current row, so I would then calculate the difference between the Changed Date values in Row 3 and Row 4 (I don't care about the values in any of the other columns for this particular requirement).
Is there a way to do this in PowerPivot? I've done a fair amount of Internet searching, and it looks like if it can be done, it would use the EARLIER or EARLIEST DAX functions, but I can't find anything that tells me how, or even if, this can be done.
Thanks.
Chris,
I have had similar requirements many times and after a really long time of trial-and-error, I finally understood how EARLIER works. It can be very powerful, but also very slow so always check for the performance of your calculations.
To answer your question, you will need to create 4 calculated columns:
1) Item Rank - used for ranking the issues with same Item ID
=COUNTROWS(FILTER('ID', EARLIER([Item ID]) = [Item ID] && EARLIER([Date]) >= [Date]))
2) Follows Error - to easily find issue that follows EROR issue
=IF([State] = "EROR",[Item Rank]+1)
3) Time of Following Issue - simple lookup so that you can calculate the different
=IF([Follows Error]>0,
LOOKUPVALUE([Date], [User], [User], [Item Rank], [Follows Error]),
BLANK()
)
4) Time Diff - calculation of time different for the specific issue
=IF([State]="EROR",
DAY([Time of Following Issue])-DAY([Date]),
BLANK()
)
With those calculated columns, you can then easily create a powerpivot table, drag State and Item Id onto the ROWS pane and then simply add Time Diff to Values. You will get an overview of issues that contain string "EROR" issue and the time it took to resolve them.
This is what it looks like in PowerPivot window:
And the resulting Pivot table:
You can download my Excel file here (2013).
As I mentioned, be careful with the performance as the calculated columns with nested EARLIER and IF conditions might be a bit too performance-demanding. If there is a smarter way, I would be very happy to see it, but for now this works for me just fine.
Also, keep in mind that all calculated columns could be nested into 1, but I kept them separated to make it easier to understand the formulas.
Hope this helps :-)

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