Tool recommendation for data transform - powerbi

Question

I have large amounts of raw fault data in Power BI.
code time status
x123 2019-04-22T23:57:00 ok
x123 2019-04-23T01:00:00 faulty
x123 2019-04-23T02:00:00 ok
x123 2019-04-23T23:00:00 faulty
x123 2019-04-24T01:00:00 ok
I need to transform this to show how long an item has been in a faulty state on a given day. So on the 23rd, the item was in a faulty state between 1 and 2a.m and then again between 11pm until past midnight.
code day % of day faulty
x123 23/04/2019 8.30% (2 hours)
Can I do this easily in Power BI or should I use another tool such as Azure Data Factory?

Answer 1

Add the following Calculated Columns to your table:
Report Date = Table1[time].[Date]
Fault Duration =
VAR CurrentTime = Table1[time]
VAR CurrentCode = Table1[code]
VAR PreviousTime =
CALCULATE (
MAX ( Table1[time] ),
FILTER (
Table1,
Table1[time] < CurrentTime &&
Table1[code] = CurrentCode
)
)
VAR NextTime =
CALCULATE (
MIN ( Table1[time] ),
FILTER (
Table1,
Table1[time] > CurrentTime &&
Table1[code] = CurrentCode
)
)
VAR FaultyFrom =
IF(
Table1[status] = "faulty",
Table1[time],
IF (
DAY(PreviousTime) = DAY(Table1[time]),
BLANK(),
Table1[time].[Date]
)
)
VAR FaultyTo =
IF (
Table1[status] = "ok",
Table1[time],
IF (
DAY(NextTime) = DAY(Table1[time]),
NextTime,
Table1[time].[Date] + 1
)
)
RETURN
IF(
ISBLANK ( PreviousTime ) || ISBLANK ( NextTime ) || ISBLANK ( FaultyFrom ),
BLANK(),
FaultyTo - FaultyFrom
)
Now create measures:
Faulty Hours = SUM ( Table1[Fault Duration] )
Faulty % Day =
IF (
HASONEVALUE ( Table1[Report Date] ),
DIVIDE (
[Faulty Hours],
DISTINCTCOUNT ( Table1[code] ),
BLANK()
),
BLANK()
)
Output:
See https://pwrbi.com/so_55825688/ for a worked example PBIX file