I have a logic app that is using a power bi query to extract data. I am trying to filter the data for previous months data only. I am getting this error. Any idea what is going on? Also, if you any other idea how I can filer a large data set for previous months data (not total or sum) please let me know.
Error I am getting: "Query (4, 1) A single value for column 'Tags - Copy.DepartmentNumber' in table 'Usage details amortized' cannot be determined. This can happen when a measure formula refers to a column that contains many values without specifying an aggregation such as min, max, count, or sum to get a single result."
What I have currently:
DEFINE
VAR CostFilter = FILTER(VALUES('Usage details amortized'[Date]), 'Usage details amortized'[Date] >= EOMONTH ( TODAY ( ), - 1 ) + 1 )
VAR Costcolumns = SUMMARIZECOLUMNS(
'Usage details amortized',
'Usage details amortized'[Tags - Copy.DepartmentNumber],
'Usage details amortized'[Tags - Copy.OwnerEmail],
'Usage details amortized'[Cost],
'Usage details amortized'[Date]
TREATAS ( CostFilter,'Usage details amortized'[Date] )
)
evaluate
Costcolumns
I believe the SUMMARIZECOLUMNS function cannot handle whole tables, it expects to encounter a single value. Right now, copy.departmentnumber, etc... all offer the expression multiple values.
Try to specify a value by aggregations like SUM, MIN, MAX, etc.
https://learn.microsoft.com/en-us/dax/summarizecolumns-function-dax
Related
I replicated an issue I am having with the 'Adventure Works DW 2020' pbix file, so if my analysis seems a little out of context, please understand this example is not the true data I am working with. The pbix I used can be downloaded here:
https://drive.google.com/file/d/1vn6CluiE5rrAF3UjYPh5ejb93H2JX6IX/view?usp=sharing
My goal is to create a measure that can flag the subset of records that I want to use for a matrix visual.
I created the following measure with notes in the syntax:
VAR TABLEVAR =
SELECTCOLUMNS(
FILTER(
SUMMARIZE(
CALCULATETABLE(Sales/*Apply several filters to Sales table*/
,NOT Sales[CustomerKey] = -1
,Sales[orderdatekey] > 20180731
,Sales[orderdatekey] < 20190601
)
,[CustomerKey]/*Count the number of products per customer*/
,"Count",COUNT(Sales[ProductKey])
)
,[Count] > 1/*Only keep customers that bought more than 1 product*/
)
,[CustomerKey] /*Select the identifiers of the desired customers*/
)
RETURN
{
SWITCH(TRUE()
,SELECTEDVALUE(Sales[CustomerKey]) IN TABLEVAR/*Flag the customers that were identified in the previous table*/
,1,BLANK()
)
}
Now, in the PowerBI Matrix visual, this seems to work at first:
I had successfully flagged the desired output. Now I just have to filter for the 'Analysis' measure to be 'Not Blank', but then this happens:
Now removing that filter and going down a level:
So you see, the measure does not evaluate at the record level of the table. Does anyone understand the concept I am missing here? I have tried all kinds of different measures but it all comes down to the same problem about flagging different levels of analysis.
Ideally, the output would only include the following(circled in green):
These are the records that are within the date filters I put into the CALCULATETABLE() arguments.
Any help or insight with this problem would be greatly appreciated. Thank you
I'm not 100% clear what you're trying to do but please try the following and see if it helps.
Analysis =
VAR TABLEVAR =
SELECTCOLUMNS(
FILTER(
SUMMARIZE(
CALCULATETABLE(Sales
,NOT Sales[CustomerKey] = -1
,Sales[orderdatekey] > 20180731
,Sales[orderdatekey] < 20190601,
REMOVEFILTERS()
)
,[CustomerKey]
,"Count",COUNT(Sales[ProductKey])
)
,[Count] > 1
)
,[CustomerKey]
)
RETURN
//CONCATENATEX(TABLEVAR, [CustomerKey], ",")
SWITCH(TRUE()
,SELECTEDVALUE(Sales[CustomerKey]) IN TABLEVAR
,1,BLANK()
)
I think I have just been staring at this for too long and have worked myself into a corner.
So let's say I have the following data:
I have locations that get monthly utility usage numbers. I want to create a clustered bar chart that shows how many months have data.
The "Merge_Use" column can have numbers, blanks, and N/A. Any number > 0 OR N/A is considered complete. 0 or blank is incomplete.
I want a clustered bar chart that shows % complete, and is split by quarter and metric type, that shows the global total % complete, but can be filtered to show the % complete by region or individual location (relationships for TRT_ID to region is housed in a separate table). For some reason I can't wrap my mind around the measure that would do that.
This was my first try. I used a calculated column, but it wasn't until after I got to the visual stage that I realized that my calculated column is static and won't be affected by filtering. (It sounds silly now but I made a column that assigned each completed field a % out of the total fields, i.e. 1/total # rows, thinking I could just sum these together in the visual).
How would you do this?
I may have solved my own problem.
I added a conditional column with Yes/No for "completed" based off my criteria. (i.e. if "" then "No", else "Yes")
Then added the following measure:
% YES =
DIVIDE (
CALCULATE ( COUNT ( Leadership_Usage_Tracking_v2[Completed] ), Leadership_Usage_Tracking_v2[Completed] = "YES" ),
CALCULATE ( COUNT ( Leadership_Usage_Tracking_v2[Completed] ), ALLSELECTED ( Leadership_Usage_Tracking_v2[Completed] ) )
)
Seems to be working so far!
For each id, I have a count of images column and check column
and my conditions are :
1)a count of images should be 8
2)In the check column for all 8 images, it should be valid then the result is No anamoly.
if I have anyone of stint is invalid/blank the result is anamoly found
please provide a condition/logic by writing a DAX query in powerbi. I need result as a measure in the report.
Measure = if(
CALCULATE(
COUNT(Table1[check]),
FILTER(Table1,
[check]="valid")
)=8,
"No anamoly","anamoly found "
)
You will need to transform your a bit. In transform query you will need to fill down the ID field, this is important because you will use it in creating a table where you will drag the measure into.
The measure:
measure _x = calculate(countrows(Table[1]), filter(Table[Check] = "valid")))
Then you can write a helper measure:
mearsure _y = if(measure _y = 8 , "No Anomaly", "Anomaly found")
Using DAX to identify first instance of a record
I'm faced with trying to identify the first instance in a database where someone (identified by the ID column) has purchased a product for the first time. It's possible for said person to purchase the product multiple times on different days, or purchase different products on the same day. I drummed up an excel formula that gets me there, but am having trouble translating into DAX.
=COUNTIFS(ID,ID,PurchaseDate,"<="&PurchaseDate,Product,Product)
Which results in the correct values in the "First Instance?" Column.
Ideally I won't have to hardcode values, as I would like to use the "Product" column as a parameter in the future. If there are other suggests aside from translating this in DAX, that would also be appreciated! (IE using filters, or other tools in PowerBI)
Thanks in advance!
This is very similar to an answer I gave to another question (which you can find here).
In that question, the request was to see a running count of rows for the given row's criteria (product, year, etc.). We can modify that slightly to get it to work in your problem.
This is the formula I provided in the answer I linked above. The basic concept is to use the EARLIER functions to get the value from the row and pass it into the filter statement.
Running Count =
COUNTROWS(
FILTER(
'Data',
[ProductName] = EARLIER([ProductName]) &&
[Customer] = EARLIER([Customer]) &&
[Seller] = EARLIER([Seller]) &&
[Year] <= EARLIER([Year])
)
)
What I would suggest for your problem is to create this as a TRUE/FALSE flag by simply checking if the running count is 1. This formula will evaluate to a Boolean flag.
First Instance =
COUNTROWS(
FILTER(
'Data',
[ID] = EARLIER([ID]) &&
[Product] = EARLIER([Product]) &&
[Purchase Date] <= EARLIER([Purchase Date])
)
) = 1
I have got this following SQL query that gives me the correct value from the database.
SELECT
SUM( DISTINCT_ORDER_NUMBERS )
FROM
(
SELECT STORE_KEY,
COUNT( DISTINCT TRANSACTION_NUM ) AS DISTINCT_ORDER_NUMBERS,
DATE_KEY,
TRANSACTION_TYPE_KEY
FROM Pos_Data
GROUP BY STORE_KEY,
DATE_KEY,
TRANSACTION_TYPE_KEY
)
AS A
I am however facing challenges writing a DAX formula for a measure in Power BI Here is what I have tried so far but I get an error.
Total Number Of Orders
VAR _TotalOrders =
SUMMARIZE('Pos_Data',
'Pos_Data'[STORE_KEY],
'Pos_Data'[DATE_KEY],
'Pos_Data'[TRANSACTION_TYPE_KEY],
"DISTINCT_ORDER_NUMBERS",
DISTINCTCOUNT('Pos_Data'[TRANSACTION_NUM]))
RETURN SUM(_TotalOrders[DISTINCT_ORDER_NUMBERS])
Please assist
The SUM function expects a base table rather than a calculated table.
Try this instead:
VAR _TotalOrders =
SUMMARIZE('Pos_Data',
'Pos_Data'[STORE_KEY],
'Pos_Data'[DATE_KEY],
'Pos_Data'[TRANSACTION_TYPE_KEY],
"DISTINCT_ORDER_NUMBERS",
DISTINCTCOUNT('Pos_Data'[TRANSACTION_NUM]))
RETURN SUMX(_TotalOrders, [DISTINCT_CHECK_SEQ])
Edit: If the difference you mentioned is related to nulls, then try this in place of DISTINCTCOUNT.
COUNTAX( DISTINCT( 'Pos_Data'[TRANSACTION_NUM] ), 'Pos_Data'[TRANSACTION_NUM] )
The COUNTAX function (as opposed to COUNTX) does not count nulls.