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Objective:
Pull data from ADO to create a burndown of story points and then forecast down to 0.
Problem:
Pulling in 3 levels of hierarchies: Epic > Feature > Story over several months.
The end date is "Today".
What I've tried:
I started out using a calculated column on a dynamic table that extended out a year and that worked, except it wouldn't filter story points since it's already loaded.
I attempted to use the same concepts in a measure, however the data stops when filters are used:
Left: Unfiltered; Right: Filtered
The measure for "_xd effort" in case it matters.
There's 2 tables: one is a dynamic table that extends out a year ('DateTable'), the other is the table from ADO('Features - Historical').
I was hoping that if the difference was a negative, then it would just add the data. There is no relationship between
_xd dailyEffort =
var _effActual = CALCULATE(SUMX('Team - Features - Historical','Team - Features - Historical'[dailyEffort]))
var _dateDiff = SUMX('DateTable',DATEDIFF([_m StartDay],[Date],DAY))
var _a = CALCULATE(if(_dateDiff > 0,999+_dateDiff,_effActual))
RETURN _a
The forecast tool in the analytics tab is not entirely reliable as sometimes it shows , and sometimes it doesn't, I suspect we reach the limit of data points. Extending the trend line to 0 would be an option as well, but that's not an optin that exists as far as I can tell.
Solved! Go to Solution.
Solved my issue:
one of the issues was that the relationship between the Date table and the History table was bi-directional, changing it to one way helped.
for future me: below is the DAX measure I'm now using. It copies the actual data until it gets to future dates, in which case it begins subtracting (forecasting), though that part is still under construction. More importantly, this works with filters so regardless of what is used on the visuals, it updates accordingly.
_mefCombo =
//variables
var maxDate = CALCULATE(MAXX('Team - Features - Historical',[Date]),FILTER(ALL('Team - Features - Historical'),[Date]))
var calcEffMaxDate = CALCULATE(SUM('Team - Features - Historical'[dailyEffort]),'DateTable'[Date] = maxDate)
var _dateDiff = (SUMX('DateTable',DATEDIFF([_m StartDay],[Date],DAY)))
var _forecast = calcEffMaxDate - _dateDiff
var _forecastRate = calcEffMaxDate - 1
var _forecast0 = if(_forecast <= 0,0,_forecast)
//return
var _dateCheckEff = if(
CALCULATE(SUMX('DateTable',[Date])) <= [_m StartDay],
[_mef TotalEffort],
_forecast0
)
return _dateCheckEff
I'll provide usable data for my next question.
Solved my issue:
one of the issues was that the relationship between the Date table and the History table was bi-directional, changing it to one way helped.
for future me: below is the DAX measure I'm now using. It copies the actual data until it gets to future dates, in which case it begins subtracting (forecasting), though that part is still under construction. More importantly, this works with filters so regardless of what is used on the visuals, it updates accordingly.
_mefCombo =
//variables
var maxDate = CALCULATE(MAXX('Team - Features - Historical',[Date]),FILTER(ALL('Team - Features - Historical'),[Date]))
var calcEffMaxDate = CALCULATE(SUM('Team - Features - Historical'[dailyEffort]),'DateTable'[Date] = maxDate)
var _dateDiff = (SUMX('DateTable',DATEDIFF([_m StartDay],[Date],DAY)))
var _forecast = calcEffMaxDate - _dateDiff
var _forecastRate = calcEffMaxDate - 1
var _forecast0 = if(_forecast <= 0,0,_forecast)
//return
var _dateCheckEff = if(
CALCULATE(SUMX('DateTable',[Date])) <= [_m StartDay],
[_mef TotalEffort],
_forecast0
)
return _dateCheckEff
I'll provide usable data for my next question.
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Do not include sensitive information or anything not related to the issue or question.
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Please show the expected outcome based on the sample data you provided.
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