I've got a number of rows and I want to calculate the difference per date.
So say I have the following:
[Date] [Transaction Number] [Value]
1 Jan 16 1 1000
2 Jan 16 1 980
I then want a fact that for every row will compare the value with the measure from the previous date.
So If I have a measure on SUM(Value) for the current date, I basically want SUM(CurrentDate) - SUM(PreviousDate) to see the movement.
A couple of things to note:
There will actually be a couple of comparisons: previous date, previous month end, previous year end.
I want this as a calculated measure not column so that I do not need to filter on the transaction number in the previous period.
What I've tried but it just comes up empty:
Previous Value :=CALCULATE(SUM(Table[Value])) - CALCULATE(SUM(Table[Value]), FILTER(Table, Table[Date] = PreviousDay(Table[Date])))
Unfortunately I cannot tell why your measure didn't work, but following should:
Previous Value := CALCULATE(SUM(Table[Value]) - CALCULATE(SUM(Table[Value]), PREVIOUSDAY(Table[date])))
Related
I am trying to create a calculated column on a SSAS cube to work out the following:
Net Net X Rate = [Net Net Revenue] / [X]
where X = no of days
I need an output for X (using MDX), Something like the no. of days for the date period selected
For example upon the selection of
30 days for the chosen month of April 2021
X = 30
rate for 30 days
14 days for the chosen month of December 2020
X=14
rate for 14 days
I don't have access to SSAS at this point, but maybe somthing like
Net Net X Rate = [Net Net Revenue] / COUNT( EXISTING [Date].[Calendar].[Day].Members )
Answered here maybe: Count children members in MDX
Maybe this could help: DateDiffDays or .
I had something like this in mind: DateDiffDays([Measures].[From_Date], Now()). It will count the days difference between some day in the past and now. DateDiffWorkdays will get you a number of working days between two dates.
Alternatively, you could pre-calculate this value in a view and then pull the number into a cube.
Assuming your Date dimension is on day granularity, a very efficient way from query performance point of view to get what you want would be to add a column to your date dimension table. This could either be done in a view in the relational data model, or in the DVS as a calculated column. Name it e. g. number of days or just X, and make it be the value 1 on each row, i. e. the column expression is just 1. Then you create a new measure group based on this table, with the only measure being X, which would just sum this column. Then, whatever your query context would be, the X measure would just be the number of days. If you want, you can then make the measure invisible.
Teradata DB
I am having a rough go at it. I have a dataset and I want to create a customer journey. The rules are that the first transaction is a journey. The next transaction that is at least 30 days out is a journey. The next transaction at least 30 days past that is also a journey. I do not have access to programming, only regular queries.
There are a few scenarios.
Customer has just 1 transaction in the dataset. Since it is the only one, it is flagged as a journey.
Customer has 2 transactions within 5 days. The first one is a journey and the second one is not since it is within 30 days.
Customer has 2 transactions. 1/1 and 2/5. They are > 30 days apart so each is flagged as a journey.
Customer has 3 transactions. 1/1, 1/8, 2/5. The first and third are journeys and the second one is not (since it is within the 30 day window of a previously flagged journey).
I have tried everything, but there always seems to be some scenario that doesn't work.
I have the logic that I can write down, but I can't figure out how to do it in teradata.
If trans_idx=1 then journey flag = y
If date - previous trans_idx date > 30 then journey_flag = Y
This is what I can get right. I can't get the sql right for the following logic. If date - previous trans_idx date < 30 then I need to accumulate the difference and then sum the next row. If it is still < 30 I need to accumulate and sum the next row. Once it gets past 30, I need to set that rows' journey flag to Y.
This works but it only compares the previous row. If I change it to unbounded, it will look at all the rows for the given sequence - i just need it to go back to previous 30 day end.
WHEN RUNNING_SUM_FLOAT=0 THEN 'Y'
WHEN RUNNING_SUM_FLOAT - MIN(RUNNING_SUM_FLOAT)
OVER (partition by sequence_id ORDER BY trans_idx
ROWS BETWEEN 1 PRECEDING and 1 PRECEDING) >=30
THEN 'Y'
ELSE 'N'
END as journey_flag
I have a fact table with 1 row for each day. Example:
ID Date Value
1 20190101 10
1 20190102 15
2 20190101 31
If I take a simple Value average in SSAS cube I get:
ID Average <Formula>
1 12.5 (10+15)/2
2 15.5 31/2
As I understand, 15.5 is there because in total there are 2 days in the scope as only two days exist in the fact data when I select the whole month.
However, I need to calculate a monthly average instead. It should check that there are 31 days in that month (based on Date dimension) and get this result:
ID Average <Formula>
1 0.8 (10+15)/31
2 1 31/31
So far I've tried to create some "fake rows" if my data, for example I've tried to create rows with Value = 0 for dates 20190103-20190131 for ID=1.
This works, it forces the calculation for ID=1 to always take all days in the period, but it messes up my other calculations in the cube.
Any other ways to force average calculation in SSAS multidimensional cube to always calculate for the entire month?
If you want to do the calculation in the Cube, you can use the Descendants function on your Date dimension
For eg., the following gives the number of days in a month using the AdventureWorks sample
WITH MEMBER Measures.DayCount AS
Descendants
(
[Date].[Calendar].CurrentMember,
[Date].[Calendar].[Date],
LEAVES
).Count
SELECT [Measures].[DayCount] ON 0,
[Date].[Calendar].[Month].ALLMEMBERS ON 1
FROM [Adventure Works]
I would recommend:
select id, eomonth(date) as eom,
sum(value) * 1.0 / day(eomonth(date)) as average
from t
group by id, eomonth(date);
EOMONTH() returns the last day of the month. You can extract the day to get the number of days in the month.
The * 1.0is because SQL Server does integer division. Your numbers look like integers, but if you are getting 15.5, then you actually have numerics or something other than an integer.
I have a DimDate table that has a Billable Day Portion field that can be between 0 and 1. For each day that's in the current Bonus Period I want to multiple that Day Portion by 10, and then return the total sum.
To find out what Bonus Period we're in, I return ContinuousBonusPeriod where the date equals today:
Current Continuous Bonus Period:= CALCULATE(MAX(DimDate[ContinuousBonusPeriod]), FILTER(DimDate, DimDate[DateKey] = TODAY()))
I can see in the measure display this is correctly coming back as Bonus Period 1. However, when I then use ContinuousBonusPeriod in the measure to determine the number of days in the current period, it only returns 10, 1 day multiplied by the static 10.
Billable Hours This Period:= CALCULATE(SUMX(DimDate, DimDate[Billable Day Portion] * 10), FILTER(DimDate, DimDate[ContinuousBonusPeriod] = [Current Continuous Bonus Period]))
It appears to be only counting today's DimDate record instead of all the records whereContinuousBonusPeriod = 'Bonus Period 1' as I'd expect.
I needed to make sure no existing filter was applied to the DimDate table when calculating the Current Continuous Bonus Period:
Current Continuous Bonus Period:= CALCULATE(MAX(DimDate[ContinuousBonusPeriod]), FILTER(ALL(DimDate), DimDate[DateKey] = TODAY()))
(Notice the ALL() statement)
I have a Month Column with the Month Field populated for each line for the 100K of lines of data I have.
I need to count the amount of times the Month Field is populated in the Previous Month (Period).
I also need to count the total amount of times the Month Field is populated in the Previous 11 months as well.
This is a rolling count for each months reporting that I do..
table name: 'ws pds' and field name [Month Tagged]
You can utilize the powerful time intelligence functions in DAX such as PARRALLELPERIOD to look at values from previous months. But in order to make use of these functions you need to create a calendar/date entity. Mark that entity as a Date table. And join to it by date from your "ws pds" table. The Date dimension should span the timeframe of your date with a continuous list of dates, one row per day.
Then your measure could look like this:
PreviousMonthCount=
CALCULATE (
COUNTROWS ( 'ws pds' ),
'ws pds'[Month Tagged] <> BLANK (),
PARALLELPERIOD ( Calendar[Date], -1, MONTH )
)