Latest BreakEven DAX Expression Value

[sentsara]

Hi,

I need to derive "LATEST Break Even" Dax Expression  based on calculated column "Rate Vs Breakeven"

DataSet name: QBM

Rate Vs Breakeven = if([Current Rate 2019]=0,blank(),if(ISBLANK([Current Rate 2019]),blank(),[Current Rate 2019]-[Monthly Break Even]))

Tried with below Expression and thrown "Expression refers to multiple column.Multiple column cannot be converted into scalar value"

LATEST Break Even=CALCULATE(MAX([Rate Vs Breakeven],ALL('QSI By Measure')))

Basically i need Lastest break even value should be repeated based on Max of "Rave vs Breakeven"

TRENDMONTH	Current Rate 2019	Monthly Break Even	Rate Vs Breakeven	LatestBreakeven	Static Final Rate
1	0.67%		0.67%	0.21%	0.423357664
2	4.29%	5.42%	-1.13%	0.21%	0.423357664
3	7.48%	7.64%	-0.16%	0.21%	0.423357664
4	10.74%	10.54%	0.20%	0.21%	0.423357664
5	12.54%	12.33%	0.21%	0.21%	0.423357664
6		14.14%		0.21%	0.423357664
7		15.46%		0.21%	0.423357664
8		16.48%		0.21%	0.423357664
9		15.93%		0.21%	0.423357664
10		18.35%		0.21%	0.423357664
11		19.42%		0.21%	0.423357664
12		19.61%		0.21%	0.423357664
13		19.61%		0.21%	0.423357664
14		21.87%		0.21%	0.423357664
15		28.71%		0.21%	0.423357664
16		43.36%		0.21%	0.423357664
17		44.34%		0.21%	0.423357664
18		44.34%		0.21%	0.423357664

[v-juanli-msft]

Hi @sentsara

Try this 

lastest = CALCULATE(MAX([TRENDMONTH]),FILTER(ALL('Latest BreakEven'),[Current Rate 2019]<>BLANK()))

LatestBreakeven = CALCULATE(MAX([Rate Vs Breakeven]),FILTER(ALL('Latest BreakEven'),[TRENDMONTH]=[lastest]))

Best Regards

Maggie

[Phil_Seamark]

HI @sentsara

Is this what you are after?

Column = 
VAR LatestTrentMonth = MAXX(FILTER('QBM','QBM'[Current Rate 2019]>0),'QBM'[TRENDMONTH])
RETURN MAXX(FILTER('QBM','QBM'[TRENDMONTH] = LatestTrentMonth),'QBM'[Rate Vs Breakeven])

[sentsara]

[sentsara]

hi phil,

I'm getting "Circular  Dependency was detected: QBM[Column]

I need the below values:

LatestBreakeven
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%
0.21%