I cant figure out the issue why my Measure query is not able to fetch data.
Let me Explain The Data Structure.
My Data Table, Contains several columns but specially mentioning 3 column names because I want my query to fetch data from these columns based on the slicer selection.
Vacation Status N
Vacation Status N2
Vacation Status N3
{
Test Date =
IF([SelectedFdate]="Vacation Status N",CALCULATE(COUNTROWS(Data),Data[Branch]="Al Ain OPS",Data[Vacation Status N]="OnDuty")+0,
IF([SelectedFdate]="Vacation Status N2",CALCULATE(COUNTROWS(Data),Data[Branch]="Al Ain OPS",Data[Vacation Status N2]="OnDuty")+0,
if([SelectedFdate]="Vacation Status N3",CALCULATE(COUNTROWS(Data),Data[Branch]="Al Ain OPS",Data[Vacation Status N3]="OnDuty")+0,0)))
}
SelectedFdate is the measure of selected value of a slicer and then I used this value to compare and fetch the data accordingly.
But my measure works well only if SelectedFdate = Vacation Status N, and it shows zero results for other selections.
Any suggestions?
SelectedFdate fetch the data from the data based on the slicer selection.
Slicer downdown is list of 3 items
Today
+1 Day
+2 Day
below is the table from where measure [SelectedFdate] fetches the result
{SelectedFdate = SELECTEDVALUE('Selected Date'[FVType],"No Selection")}
Related
My Data is in weekly buckets. I want to split the number into a monthly number but, since there is an overlap in days falling in both the months, I want a weighted average of the data in terms of days that fall in each of the months. For example:
Now, in the above picture, I want to split that 200 (5/7*200 in Jan, 2/7 in Feb). How can I do that using Excel/ Power Pivot/ Dax Functions? Any help here is much appreciated.
Thank you!
Assuming your fact table looks something like below. Values are associated with the starting date of the week it occurred.
Although it may actually be a more granular data, having multiple rows for each week with additional attributes (such as identifiers of a person, a store, depending on the business), what being shown below will work the same.
What we need to do first is to create a date table. We can do that in "Design" tab, by clicking "Date Table", then "New".
In this date table, we need to add a column for starting date of the week which the date of each row is in. Set the cursor to "Add Column" area, and input following formula. Then rename this column to "Week Start Date".
= [Date] - [Day Of Week Number] + 1
Now, we can define the measure to calculate the number allocated to each month with following formula. What this measure is doing is:
Iterating over each row of the fact table
Count the number of days for the week visible in the filter context
Add the value portion for the visible days
Value Allocation := SUMX (
MyData,
VAR WeekStartDate = MyData[Week]
VAR NumDaysInSelection = COUNTROWS (
FILTER (
'Calendar',
'Calendar'[Week Start Date] = WeekStartDate
)
)
VAR AllocationRate = DIVIDE ( NumDaysInSelection, 7 )
RETURN AllocationRate * MyData[Value]
)
Result in the pivot table will be looking like this.
I have 2 large tables in power pivot and I am trying to reconcile stockpile build grades to crushed stockpile grades. Please see example. I can create pivot table that contains the crushed grades but I am unable to find the right way to bring the stockpile grades though for the reconciliation high lighted in green in the attached example.
Thanks for any help or direction on where to look
In Power Query, create your lookup tables.
1) unique crushers, ID
2) Dates, ID
Here is a function to create a dates table, if you need one. After you invoke the function to get the column of dates, add another column for the ID.
/*--------------------------------------------------------------------------------------------------------------------
PQ Create a Dates Table, returning a single column of dates.
Inputs:
Start Date | Enter the year as yyyy, month as mm, day as dd
End Date | Enter the year as yyyy, month as mm, day as dd
Increments | One row will be returned per increment.
Author: Jenn Ratten
Edits:
07/16/18 | Modified query copied from the internet.
10/01/19 | Converted to a function.
--------------------------------------------------------------------------------------------------------------------*/
let
fDatesTable = (StartYear as number, StartMonth as number, StartDay as number, EndYear as number, EndMonth as number, EndDay as number, IncrementDays as number, IncrementHours as number, IncrementMin as number, IncrementSec as number) as table =>
let
StartDate = #date(StartYear,StartMonth,StartDay),
EndDate = #date(EndYear,EndMonth,EndDay),
Increments = #duration(IncrementDays,IncrementHours,IncrementMin,IncrementSec),
DatesTable = Table.FromColumns({List.Dates(StartDate, Number.From(EndDate) - Number.From(StartDate), Increments)}, type table[Date]),
ChangeType = Table.TransformColumnTypes(DatesTable,{{"Date", type date}})
in
ChangeType
in
fDatesTable
Load all of the tables to the data model.
Go to Power Pivot, diagram view, and create your relationships.
Lookup Crusher to data tables 1 and 2
Lookup Date to data tables 1 and 2
Go to Data View on data tables 1 and 2, add 2 new columns for the lookup IDs. You can specify the column header and the formula at one time by clicking in first cell and using this syntax, then either press enter or click the check mark in the formula bar.
Dates Lookup ID:=RELATED(lookup_dates[ID])
Crusher Lookup ID:=RELATED(lookup_crusher[ID])
Optional, but a good practice....
Right-click the new fields you just created and select "hide from client tools". Also hide the date and crusher fields on both data tables, and the ID field on both lookup tables. When you are creating pivots to summarize data from more than one table, the text fields that you place on your pivot table should be the fields that are shared (aka the lookup tables). This helps to minimize pivots in which the grand totals don't match the sum that you actually see on the table. If you hide the fields, it reminds you of that. There are exceptions of course, but this is a good rule of thumb.
Now create measures to sum the tons and any other math calculations you'd like. With the measures, start simple and let the pivot do the slicing. Put the measures in the values section of the pivot table.
Sum of Source Tons:=sum(Table1[Tons])
Sum of Destination Tons:=sum(Table2[Tons])
In Excel connected to SSAS, I am trying to build a pivot table and add a custom Measure Calculation using "OLAP Tools" and/or "OLAP Pivot Table Exensions". I am trying to add a calculation that is really simple in my mind, but I cannot get it to work. The calc I need is:
GOAL: A record count of the [Items] dimension records grouped by any of the
[Items] dimension fields.
In particular I am trying to group by [Items].[Items Groups] and [Items].[Item]. Item is the lowest grain, so the count should return value "1". I have created a couple calculations that are kind of in the ballpark (see below). But the calcs don't appears to be working as desired.
What I have tried:
Attempt #1 -- [Measures].[Items Count (With net amount values)]
DISTINCTCOUNT( {[Items].[Item].MEMBERS} )
The calc 'Items Count (With net amount values)' appears to be
returning a decent count value, but it appears it only counts the Item
if there are transnational records found (not sure why). Also, when
at the lowest grain level the calc returns that value for the parent
group, not the dimension level selected on the rows.
Attempt #2 -- [Measures].[Items Count (All)]
[Items].[Item].[Item].Count
This calc returns the TOTAL item count for the entire dimension
regardless of the dimension level placed on the rows.
Attempt #3 -- [Measures].[Items Count]
COUNT ( { [Items].[Item].MEMBERS}, EXCLUDEEMPTY)
This calc freezes up Excel and I have to quit Excel. No idea why. I have seen this sytnax recommended on a few different sites.
Screenshot:
Help please? This seems really simple, but I am not very skilled with MDX. In DAX and SSAS TABULAR this would be very simple expression. But I'm struggling to count the rows with MDX in SSAS MD.
The "Outside Purchased Beef" group has 18 items with transactions, but 41 items in total. I do not know how to calculate the "41" value.
SSAS Excel-CalcMeasure-CountRows.png
Take a look at the following samples on AdventureWorks.
with member [Measures].[CountTest]
as
count(existing [Product].[Subcategory].members - [Product].[Subcategory].[All])
select
{
[Measures].[Internet Sales Amount],[Measures].[CountTest]
}
on columns,
{
([Product].[Category].[Category]
,[Product].[Subcategory].[Subcategory] -- comment this line for the second result
)
}
on rows
from [Adventure Works]
Now comment the indicated line for the parent view.
When displaying prior month sales, I noticed that items with no sales in current month are missing in the Pivot Table output of the data model. However, the grand total sales includes sales of those missing items.
I created a small data model to replicate the issue: 2 tables (1 sales table and 1 calendar table) and it has 1 single DAX formula:
Previous Month Sales:=CALCULATE(sum([Sales]),PREVIOUSMONTH(Sales[Date]))
In the output table, I would have expected 1 more item row for Potatoes, with 0 sales in current month and 31 in previous month.
Is there a way to force-show Potatoes item in the pivot table above when selecting date 24/03/2019? Can this be achieved with DAX formulas?
You need to use the Date field from your Calendar (Date) table, for Time Intelligence to work as you intend:
So change your Previous Month Sales measure to:
Sales Previous Month:=CALCULATE (
SUM ( Sales[Sales] ),
PREVIOUSMONTH ( Calendar[Date] )
)
I'd also recommend creating an Explicit Measure for Sales:
Sales Total:=SUM ( Sales[Sales] )
Now you can recreate your pivot output, using Date field(s) from Calendar in your slicer / filter, and you should get the output you require:
I have a table in SSAS tabular mode that shows how individual pieces of products moved through different sections of a production line:
Product_ID, section_ID, Category_id (product category), time_in (when a product entered the section), time_out (when the product exited the section)
This is how the input table looks like:
I would like to write a measure in DAX that can show me the stock of each section and product category day-by-day as shown below by counting the number of distinct product ids which were in a particular section on that day.
I'm using SQL Server 2017 Analysis Services in Tabular Mode and Excel Pivot Table for representation.
Create a new table that has all of the dates that you want to use for your columns. Here's one possibility:
Dates = CALENDAR(MIN(ProductInOut[time_in]), MAX(ProductInOut[time_out]))
Now create a measure that counts rows in your input table satisfying a condition.
ProductCount =
VAR DateColumn = MAX(Dates[Date])
RETURN COUNTROWS(FILTER(ProductInOut,
ProductInOut[time_in] <= DateColumn &&
ProductInOut[time_out] >= DateColumn)) + 0
Now you should be able to set up a pivot table with Category_id on the rows and Dates[Date] on the columns and ProductCount as the values.