I have forecast and budget values for the year, and a new forecast is created every quarter. I need PowerBI to pick up the Metric Value (can be Budget, Q1F, Q2F and Q3F) for a given date based on data availability.
Example - If for a given date, data for Q3F is available, pick Q3F, else pick Q2F else Q1F else budget.
This is what my data looks like:
Date Metric Value
1/1/11 Budget 1.1
1/1/11 Q3F 1.2
1/1/11 Q2F 1.3
In this case the function should pick up Q3F since it's available.
One way to solve this would be by using both a SUMX and a SWITCH Statements.
To start with assign a constant to your forecasts, e.g. budget = 1, Q1F = 2 and so on as a column on your data. The idea more recent forecast will have a higher number, it will be used in the switch statement late. I am going to refer to it as forecast_ID in this example.
I am also assuming you have a calendar table, also that your forecasts are entered in entirely for the business and not in waves. E.g. Category A is still on budget, Category B is an updated forecast.
The idea of below, is that the SUMX iterates though each quarter that you are looking at, e.g. 2018 would run Q1, Q2, Q3, Q4 separately.
Within the context of each quarter, it is getting the MAX of your forecast IDs, which is then used in the switch to select the most recent forecast.
Measure :=
SUMX (
VALUES ( Calendar[Quarter] ),
SWITCH (
MAX ( table1[forecast_ID] ),
1, CALCULATE ( SUM ( table1[value] ), table1[Metric] = "Budget" ),
2, CALCULATE ( SUM ( table1[value] ), table1[Metric] = "Q1F" )
)
)
You could also then do something like MAX ( table1[forecast_ID] - 1) for finding the previous forecast dynamically.
If you always want to pull the most recent value then you can use LASTNONBLANK
As Marcus mentioned, the first step is to create a constant for your forecasts. I set up a separate table for this example.
Then you can create a relationship between the two tables based on Metric. Add a calculated column to your original table
MetricConstant = RELATED(Table2[Constant])
Now create a measure to pull the most recent value within each date period
Measure =
SUMX (
VALUES ( Table1[Date] ),
CALCULATE ( SUM ( Table1[Value] ), LASTNONBLANK ( Table1[MetricConstant], 1 ) )
)
Now when you pull in the Date and the Measure it will only show you the most recent available
EDIT-Updated based on comments. If you want to view which Metric is being used you need another measure
MetricMeasure = CALCULATE(MAX(Table1[Metric]),LASTNONBLANK(Table1[MetricConstant],1))
You could create an area chart based on that, and add this to the tooltip.
Related
My intention is to populate days of the month to simulate a data warehouse periodic snapshot table using DAX measures. My goal is to show non-additive values for the quantity.
Consider the following transactions:
The granularity of my snapshot table is day. So it should show the following:
Take note that a day may have multiple entries but I am only interested in the latest entry for the day. If I am looking at the figures using a week period it should show the latest entry for the week. It all depends on the context fixter.
However after applying the measure I end up with:
There are three transactions. Two on day 2 and the other on day 4. Instead of calculating a running total I want to show the latest Qty for the days which have no transactions without running accumulating totals. So, day 4 should show 4 instead of summing up day 3 and day 4 which gives me 10. I've been experimenting with LASTNONBLANK without much success.
This is the measure I'm using:
Snapshot =
CALCULATE(
SUM('Inventory'[Quantity]),
FILTER(
ALL ( 'Date'[Date] ),
'Date'[Date] <= MAX( 'Date'[Date] )
)
)
There are two tables involved:
Table # 1: Inventory table containing the transactions. It includes the product id, the date/time the transaction was recorded and the quantity.
Table # 2: A date table 'Date' which has been marked as a date table in Power BI. There is a relationship between the Inventory and the Date table based on a date key. So, in the measure, 'Date'[Date] refers to the Date column in the Date table.
You can use the LASTNONBLANKVALUE function, that returns the last value of the expression specified as second parameter sorted by the column specified as first parameter.
Since LASTNONBLANKVALUE implicitly wraps the second parameter into a CALCULATE, a context transition happens and therefore the row context is transformed into the corresponding filter context. So we also need to use VALUES to apply the filter context to the T[Qty] column. The returned table is a single row column and DAX can automatically convert a single column, single row table to a scalar value.
Then, since we don't have a dimension table we have to get rid of cross-filtering, therefore we must use REMOVEFILTERS over the whole table.
the filter expression T[Day] < MaxDay is needed because LASTNONBLANKVALUE must be called in a filter context containing all the rows preceding and including the current one.
So, assuming that the table name is T with fields Day and Qty like in your sample data, this code should work
Edit: changed in order to support multiple rows with same day, assuming the desired result is the sum of the last day quantities
Measure =
VAR MaxDay =
MAX ( T[Day] )
RETURN
CALCULATE (
LASTNONBLANKVALUE (
T[Day],
SUM ( T[Qty] )
),
T[Day] <= MaxDay,
REMOVEFILTERS ( T )
) + 0
Edit: after reading the comments, this might work on your model (untested)
Measure =
VAR MaxDay =
MAX ( 'Date'[Date] )
RETURN
CALCULATE (
LASTNONBLANKVALUE (
Inventory[RecordedDate],
SUM ( Inventory[Quantity] )
),
'Date'[Date] <= MaxDay
) + 0
I need to show how many active contracts we have open for each month in the last 6 months. I am trying to figure out a way to display this. Here is my table
Machine Enrollment# StartDate EndDate
A 1 1/2/2016 6/18/2019
B 2 12/15/2012 5/12/2034
C 3 3/25/2019 4/25/2021
D 4 1/7/2000 7/15/2019
A 5 10/1/2019 10/1/2025
I have thousands of rows. I want to be able to show a rolling 6 month visual for how many machines are under contract. So in this small example it would look like this
Apr-19 June-19 Jul-19 Aug-19 Sep-19 Oct-19
4 4 3 2 2 3
Where do I even begin in creating this? In the past, we have just looked at the numbers for the current month and tacked those results onto the end of a static table and deleted the column from over 6 months ago. I have been assigned to automate this report in Power BI. I am guessing I need to create a column/measure that looks at the EndDate and compares it to the filtered Date in the visual (ie: Aug-19) and determines if the contract was open at that time. But I do not know. Any help is much appreciated. Thanks in advance!
I think I found a solution for what you are looking for. You may find a sample pbix file here.
1. Create a calendar table
A calendar table is required to filter/slice the time periods. The calendar table needs to have a unique Date column, and optional columns such as Year, Quarter, and Month, depending on what units of period you need in the analysis.
A calendar table can be most easily created as a DAX calculated table. Here is an example of a minimal calendar table required in this use case.
Calendar =
ADDCOLUMNS(
CALENDAR( MIN( Contracts[StartDate] ), MAX( Contracts[EndDate] ) ),
"Year Month", FORMAT( [Date], "mmm-yy" ),
"Year Month Number", YEAR( [Date] ) * 100 + MONTH( [Date] )
)
2. Create a measure to calculate number of open contracts
Every numbers calculated and shown in reports need to be defined as measures.
Let's think about the number of May-19. The current filter context includes all 31 dates in the Calendar table between 2019-05-01 and 2019-05-31. In this case, how can we think of an open contract? If the contract starts after 2019-05-31, it is not open. If the contract ends before 2019-05-01, it is not open as well. Therefore the open contract meets this condition.
Starts on or before 2019-05-31 and
Ends on or after 2019-05-01
Below is the measure definition to count the number of contracts based on this condition.
# Open Contracts =
VAR MinDate = MIN( 'Calendar'[Date] )
VAR MaxDate = MAX( 'Calendar'[Date] )
RETURN COUNTROWS(
FILTER(
Contracts,
Contracts[StartDate] <= MaxDate
&& Contracts[EndDate] >= MinDate
)
)
3. Add dynamic filter for last 6 months
If I was understanding correctly, the requirement is to show monthly number of last 6 calendar months, excluding this month. I could not find a straightforward way for this. My solution may contain a bit of hacky scent.
Power BI does not have built-in filter support based on calendar months relative to now. We need to build a custom logic to achieve this. I did it by creating a measure that indicates whether current filter context is within the desired period. This measure is a flag that returns 1 if the filter context is a single calendar month which is included in the last 6 calendar months, or returns BLANK otherwise.
__Last6MonthFlag =
VAR YearMonths = CALCULATETABLE(
VALUES( 'Calendar'[Year Month] ),
REMOVEFILTERS( 'Calendar'[Year Month] ),
'Calendar'[Date] > EOMONTH( TODAY(), -7 )
&& 'Calendar'[Date] <= EOMONTH( TODAY(), -1 )
)
RETURN IF(
HASONEVALUE( 'Calendar'[Year Month] )
&& SELECTEDVALUE( 'Calendar'[Year Month] ) IN YearMonths,
1
)
Then I used this measure in the visual filter like this.
You need to do below activities to achieve your requirement.
Define a calendar table holding all the dates for your report. Define a calculated column for Month-Year. Month-Year = FORMAT('CalendarTable'[Date], "MM-YYYY")
You can define a calculated measure, which will return 1 if the end date of the contract is < 6 months from current date (you can use TODAY() function). This function will help in rolling calculation based on current date. Otherwise, this calculated measure will return NULL and SUM them.
You can drag the month-Year calculated column, defined in step no. 1, to the column axis. You can drag the calculated measure, defined in step no.2, to the values section. PowerBI control by default filters out the NULL values. So, when you use the calculated measure defined in step no. 2, you will get values only for the last 6 months. As the calculation is defined based on TODAY(), it will be a running calculation.
I have the following graph created. It tracks the count of a certain even in a quarter by groups (i erased the group names and renamed them (ABC's due to sensitive data).
I need the graph to show the cumulative value that is to say for example. Q1 A=1, Q2 A=3, Q3 A=5.
I have played around with quick measures but I can't seem to make them breakdown the accumulation by group, Only quarter (Q1 =1, Q2 =6, etc).
I think i need to create a quick-measure of a quick-measure but I am not sure the order and what the measures would look like.
There are only 2 relevant fields: date_of_event and group
X axis: date of event (by year and quarter), group
y axis: count of date_of event
Thanks
For this, you'll definitely benefit from a date dimension and a dimension for your group. There are many template date dimensions out there, but I'm partial to mine. A group dimension for you may be as simple as just taking the distinct values of your existing [Group] field.
Time intelligence is basically always easier when your model is dimensionalized.
With that, you'd set up relationships as below:
'DimDate'[Date] -1:N-> 'YourEventTable'[Date_Of_Event]
'DimGroup'[Group] -1:N-> 'YourEventTable'[Group]
With that in place, you can use the built-in time intelligence functions or roll your own (examples of rolling your own in my linked date dimension repo).
Events = COUNTROWS ( 'YourEventTable' )
Events YTD = TOTALYTD ( [Events], 'DimDate'[Date] )
If you need an all-time cumulative, instead, you can use this:
Events All-time Cumulative =
VAR CurrentDate = MAX ( 'DimDate'[Date] )
RETURN
CALCULATE (
[Events],
ALL ( 'DimDate' ),
'DimDate'[Date] <= CurrentDate
)
Make sure to always use dimension fields for axis labels and such, and never the same from the fact table.
I had encounter it early this week and below is my DAX for the Cumulative total measure,
Cumulative Total =
CALCULATE (
SUMX (
Table,
IF ( DISTINCTCOUNT ( Table[UserID] ) > 0, 1, 0 ) //Put your Group Here
),
FILTER (
ALLSELECTED ( Table ),
Table[InitialAccessDate] //Date of event
<= MAX ( Table[InitialAccessDate] ) //Date of event
)
)
I hope it helps!! Cheers!!
I tried create a dashboard based on fiscal year, with more Filters, like region, sales rep name, ...
Example files avaliable on dropbox:
https://www.dropbox.com/sh/l25kdz6enmg35yb/AABPuOk3kKOpfQdKDfRUcnX2a?dl=0
On my closest attempt, i tried this follow:
Add one column on my data set, naming each period as distinct number, like: "17";"18";"19", due to deslocated fiscal year (april to march).
Then create a measure:
PREVIOUS CROP_YEAR = SWITCH(TRUE();
SELECTEDVALUE('dataset'[Crop-X])=16;(CALCULATE(SUM('dataset'[Order Value]);ALL('dataset')));
SELECTEDVALUE('dataset'[Crop-X])=17;(CALCULATE(SUM('dataset'[Order Value]);ALL('dataset')));
SELECTEDVALUE('dataset'[Crop-X])=18;(CALCULATE(SUM('dataset'[Order Value]);ALL('dataset')));
SELECTEDVALUE('dataset'[Crop-X])=19;(CALCULATE(SUM('dataset'[Order Value]);ALL('dataset')));
0)
Expected output was:
Values based on all filters applied, But instead i just get an empty charts
The measure is return the total because you are explicitly asking for it by using the ALL function. This removes all the filters from the dataset thus returning a grand total. This can work but it creates a complexity in your dataset with respect of having two time dimensions. The way to solve this is to first make sure you filter the date correctly with respect to both dimensions
PREVIOUS YEAR =
CALCULATE(
SUM('dataset'[Order Value]);
FILTER(
ALL ( 'dataset' ) ;
AND (
'dataset'[Crop-X] = MAX('dataset'[Crop-X]) -1 ;
'dataset'[YEAR] = MAX('dataset'[YEAR] ) -1
)
)
)
Furthermore, this measure still uses the ALL function which means any other filters get ignored. Using ALLSELECTED instead would result in the relative time filtering to result in nothing as soon as you select any time based slicer in your dashboard, this prevents the filter from looking at any other part of the dataset that is not within the primary sliced dataset. The workaround would be to use ALLEXCEPT and add the filters you want to be able to use as arguments. Downside is that any filter you add to your dashboard will have to be added to the exception manually.
PREVIOUS YEAR =
CALCULATE(
SUM('dataset'[Order Value]);
FILTER(
ALLEXCEPT( 'dataset' ; Dim1[Group] ; Dim1[Manager] ; Dim1[Region] ) ;
AND (
'dataset'[Crop-X] = MAX('dataset'[Crop-X]) -1 ;
'dataset'[YEAR] = MAX('dataset'[YEAR] ) -1
)
)
)
I have following scenario which has been simplified a little:
Costs fact table:
date, project_key, costs €
Project dimension:
project_key, name, starting date, ending date
Date dimension:
date, years, months, weeks, etc
I would need to create a measure which would tell project duration of days using starting and ending dates from project dimension. The first challenge is that there isn't transactions for all days in the fact table. Project starting date might be 1st of January but first cost transaction is on fact table like 15th on January. So we still need to calculate the days between starting and ending date if on filter context.
So the second challenge is the filter context. User might want to view only February. So it project starting date is 1.6.2016 and ending date is 1.11.2016 and user wants to view only September it should display only 30 days.
The third challenge is to view days for multiple projects. So if user selects only single day it should view count for all of the projects in progress.
I'm thankful for any help which could lead towards the solution. So don't hesitate to ask more details if needed.
edit: Here is a picture to explain this better:
Update 7.2.2017
Still trying to create a single measure for this solution. Measure which user could use with only dates, projects or as it is. Separate calculated column for ongoing project counts per day would be easy solution but it would only filter by date table.
Update 9.2.2017
Thank you all for your efforts. As an end result I'm confident that calculations not based on fact table are quite tricky. For this specific case I ended up doing new table with CROSS JOIN on dates and project ids to fulfill all requirements. One option also was to add starting and ending dates as own lines to fact table with zero costs. The real solution also have more dimensions we need to take into consideration.
To get the expected result you have to create a calculated column and a measure, the calculated column lets count the number of projects in dates where projects were executed and the measure to count the number of days elapsed from [starting_date] and [ending_date] in each project taking in account filters.
The calculated column have to be created in the dim_date table using this expression:
Count of Projects =
SUMX (
FILTER (
project_dim,
[starting_date] <= EARLIER ( date_dim[date] )
&& [ending_date] >= EARLIER ( date_dim[date] )
),
1
)
The measure should be created in the project_dim table using this expression:
Duration (Days) =
DATEDIFF (
MAX ( MIN ( [starting_date] ), MIN ( date_dim[date] ) ),
MIN ( MAX ( [ending_date] ), MAX ( date_dim[date] ) ),
DAY
)
+ 1
The result you will get is something like this:
And this if you filter the week using an slicer or a filter on dim_date table
Update
Support for SSAS 2014 - DATEDIFF() is available in SSAS 2016.
First of all, it is important you realize you are measuring two different things but you want only one measure visible to your users. In the first Expected result you want to get the number of projects running in each date while in the Expected results 2 and 3 (in the OP) you want the days elapsed in each project taking in account filters on date_dim.
You can create a measure to wrap both measures in one and use HASONEFILTER to determine the context where each measure should run. Before continue with the wrapping measure check the below measure that replaces the measure posted above using DATEDIFF function which doesn't work in your environment.
After creating the previous calculated column that is required to determine the number of projects in each date, create a measure called Duration Measure, this measure won't be used by your users but lets us calculate the final measure.
Duration Measure = SUMX(FILTER (
date_dim,
date_dim[date] >= MIN ( project_dim[starting_date] )
&& date_dim[date] <= MAX ( project_dim[ending_date] )
),1
)
Now the final measure which your users should interact can be written like this:
Duration (Days) =
IF (
HASONEFILTER ( date_dim[date] ),
SUM ( date_dim[Count of Projects] ),
[Duration Measure]
)
This measure will determine the context and will return the right measure for the given context. So you can add the same measure for both tables and it will return the desired result.
Despite this solution is demonstrated in Power BI it works in Power Pivot too.
First I would create 2 relationships:
project_dim[project_key] => costs_fact[project_key]
date_dim[date] => costs_fact[date]
The Costs measure would be just: SUM ( costs_fact[costs] )
The Duration (days) measure needs a CALCULATE to change the filter context on the Date dimension. This is effectively calculating a relationship between project_dim and date_dim on the fly, based on the selected rows from both tables.
Duration (days) =
CALCULATE (
COUNTROWS ( date_dim ),
FILTER (
date_dim,
date_dim[date] >= MIN ( project_dim[starting_date] )
&& date_dim[date] <= MAX ( project_dim[ending_date] )
)
)
I suggest you to separate the measure Duration (days) into different calculated column/measure as they don't actually have the same meaning under different contexts.
First of all, create a one-to-many relationship between dates/costs and projects/costs. (Note the single cross filter direction or the filter context will be wrongly applied during calculation)
For the Expected result 1, I've created a calculated column in the date dimension called Project (days). It counts how many projects are in progress for a given day.
Project (days) =
COUNTROWS(
FILTER(
projects,
dates[date] >= projects[starting_date] &&
dates[date] <= projects[ending_date]
)
)
P.S. If you want to have aggregated results on weekly/monthly basis, you can further create a measure and aggregate Project (days).
For Expected result 2 and 3, the measure Duration (days) is as follows:
Duration (days) =
COUNTROWS(
FILTER(
dates,
dates[date] >= FIRSTDATE(projects[starting_date]) &&
dates[date] <= FIRSTDATE(projects[ending_date])
)
)
The result will be as expected: