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Post Patron

## DAX help - Accounts Receivable Aging

Hello. The Cumulative Balance pattern works well for me for trending Total Accounts Receivable. But I'm having trouble adapting it to subsets of the total (e.g., by account age group). Here is the normal pattern:

IF (
MIN ( 'Date'[DateKey] )
<= CALCULATE ( MAX ( Transactions[DateKey] ), ALL ( Transactions ) ),
CALCULATE (
SUM ( Transactions[Quantity] ),
FILTER (
ALL ( 'Date'[Date] ),
'Date'[Date] <= MAX ( 'Date'[Date] )
)
)
)

And here is my attempt, which isn't working:
IF (
MIN ( 'Date'[Date] )
<= CALCULATE ( MAX ( TransactionsTable[Posting_Date] ), ALL ( TransactionsTable ) ),
CALCULATE (
SUM ( TransactionsTable[Transaction_Amount] ),
FILTER (
ALL ( 'Date'[Date] ),
'Date'[Date] <= MAX ( 'Date'[Date] )
&& DATEDIFF ( MAX ( TransactionsTable[CustomerCheckoutDate] ), 'Date'[Date], DAY ) < 31
)
)
)

My Transactions table is over 70 million rows so the proposed solution must be very performant/efficient of course.
1 ACCEPTED SOLUTION
Post Patron

Unfortunately that did not work. But luckily I stumbled on a formula that works. Here it is in case anyone is interested. I'd be happy to hear any suggestions as to improvements to this formula if any exist.

Total AR 0-30 =
VAR EndDate =
MAX ( 'Calendar'[Date] )
RETURN
IF (
MIN ( 'Calendar'[Date] )
<= CALCULATE ( MAX ('TransactionsTable'[PostingDate]), ALL ('TransactionsTable') ),
CALCULATE (
SUM ( 'TransactionsTable'[TransactionAmount] ),
FILTER ( ALL ( 'Calendar'[Date] ), 'Calendar'[Date] <= EndDate ),
KEEPFILTERS (
IFERROR (
DATEDIFF ( CustomerTable[CustomerCheckoutDate], EndDate, DAY ),
( DATEDIFF ( EndDate, CustomerTable[CustomerCheckoutDate], DAY ) ) * -1
)
< 31
)
)
)

7 REPLIES 7
Community Champion

can you share anonymized sample rows for the tables used?
is 31 the only age group you cover, or are there others, if so, what are they?

Did I answer your question? Mark my post as a solution!
Thank you for the kudos 🙂

Post Patron

Hello @Stachu. Thanks for your reply. Below is some sample data. I have a calendar table that is connected to the table below on the Transaction Date.

Ultimately I would want age groups for every 30 days up to 180 and then 180+. But I figured if I could get 0-30 figured out then I could take it from there to do the other buckets.

 Account # Item # Transaction Date Transaction Amount CustomerCheckoutDate 1 532555 3/14/2018 \$                     4,214.00 4/4/2018 1 134134 3/21/2018 \$                     1,354.00 4/4/2018 1 413443 2/6/2018 \$                     1,661.00 4/4/2018 1 412141 4/5/2018 \$                     1,838.00 4/4/2018 2 585811 2/13/2018 \$                     2,065.00 2/22/2018 2 147547 2/24/2018 \$                     4,238.00 2/22/2018 2 454787 2/9/2018 \$                     3,698.00 2/22/2018
Community Champion

hmm, can you try this?

LessThan31 =
VAR DaysOverdue =
Transactions,
"DaysOverdue", Transactions[CustomerCheckoutDate] - Transactions[Transaction Date]
)
VAR LessThan31 =
FILTER ( DaysOverdue, [DaysOverdue] < 31 )
RETURN
CALCULATE ( SUM ( Transactions[Transaction Amount] ), LessThan31 )

I wasn't clear whether you need to calculate the days on row level (current syntax) or grouped per Account/Account&Item, if grouping is possible then Summarize could replace whole Transactions table

Also the problem becones very easy once you add calculated column for

Transactions[CustomerCheckoutDate] - Transactions[Transaction Date]

the question is whether it makes sense from aggregation angle

Did I answer your question? Mark my post as a solution!
Thank you for the kudos 🙂

Post Patron

Unfortunately that did not work. But luckily I stumbled on a formula that works. Here it is in case anyone is interested. I'd be happy to hear any suggestions as to improvements to this formula if any exist.

Total AR 0-30 =
VAR EndDate =
MAX ( 'Calendar'[Date] )
RETURN
IF (
MIN ( 'Calendar'[Date] )
<= CALCULATE ( MAX ('TransactionsTable'[PostingDate]), ALL ('TransactionsTable') ),
CALCULATE (
SUM ( 'TransactionsTable'[TransactionAmount] ),
FILTER ( ALL ( 'Calendar'[Date] ), 'Calendar'[Date] <= EndDate ),
KEEPFILTERS (
IFERROR (
DATEDIFF ( CustomerTable[CustomerCheckoutDate], EndDate, DAY ),
( DATEDIFF ( EndDate, CustomerTable[CustomerCheckoutDate], DAY ) ) * -1
)
< 31
)
)
)

Employee

Hi @robarivas,

Congratulations, please mark your reply as answer, so more people will benefit from here.

Thanks,
Angelia

Employee

Hi @robarivas,

Please use the following DAX and check if you can get expected result.

=
VAR X =
MAX ( 'Date'[Date] )
RETURN
IF (
MIN ( 'Date'[Date] )
<= CALCULATE ( MAX ( TransactionsTable[Posting_Date] ), ALL ( TransactionsTable ) )
&& DATEDIFF ( MAX ( TransactionsTable[CustomerCheckoutDate] ), 'Date'[Date], DAY )
< 31,
CALCULATE (
SUM ( TransactionsTable[Transaction_Amount] ),
FILTER ( ALL ( 'Date'[Date] ), 'Date'[Date] <= X )
)
)

Best Regards,
Angelia

Post Patron

Hello @v-huizhn-msft. Thank you for the reply.  Unfortunately it kicked back the following error:

"A single value for column 'Date' in table 'Date' 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."

Below is the portion of the formula that appears to have caused the error:

=
VAR X =
MAX ( 'Date'[Date] )
RETURN
IF (
MIN ( 'Date'[Date] )
<= CALCULATE ( MAX ( TransactionsTable[Posting_Date] ), ALL ( TransactionsTable ) )
&& DATEDIFF ( MAX ( TransactionsTable[CustomerCheckoutDate] ), 'Date'[Date], DAY )
< 31,
CALCULATE (
SUM ( TransactionsTable[Transaction_Amount] ),
FILTER ( ALL ( 'Date'[Date] ), 'Date'[Date] <= X )
)
)

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