I'm trying to get Actual Sales per day using DAX howver I can't able to get the Actual Sales Per Day using DAX Expression.
I'm using below DAX to calculate Total No. of days.
b:=CALCULATE(COUNT(DimDate[Date]),DimDate[CY_Year]=YEAR(TODAY()),USERELATIONSHIP(Fact_Sales[Doc_Date],DimDate[Date]))
Please provide the correct formula.
Assuming [a] is a measure in the Data Model then you just create a new measure for Actual Sales Per Day as follows:
c :=
[a] / [b]
If [a] is not already a measure in the Data Model then create it first as follows:
a :=
SUM ( [SalesAmount] )
Related
I am trying to calculate a sum of a column for a specific calendar week, and want to compare that to the same week in the previous year.
So let's say I have the sum of WK21 for 2020 is 1000 and sum of WK21 in 2019 is 800. The field should return: 200.
Attached is how my dataset looks like.
I would like to sum the credit per WK for each segment, and see how the difference is to the sum of that week for that same segment, in the previous year. Later on I would change the difference to percentDifference, but I assume the main formula is the same.
Is that easy doable?
Tried this (percentDifference) for WoW (in the same year), and it worked using this formula:
percentDifference(sum({credit}),[{wk} ASC],-1,[{year}, industry, segment])
But when trying for weekly YoY the following formula, it didnt work (-52 because 52 weeks in year):
percentDifference(sum({credit}),[{wk} ASC, year ASC],-52,[industry, segment])
PS: for the country, I didnt take that in consideration, as I want to filter for the countries I want later on...
For Year-on-year difference create a calculated field like the following
difference(sum({credit}), [{wk} ASC, {year} ASC], -1, [{Industry}, {Segment}])
For year-on-year percentage difference your calculated field would be
percentDifference(sum({credit}), [{wk} ASC, {year} ASC], -1, [{Industry}, {Segment}])
This is because the lookup index in the function (-1) is based on the sort of the rows (sort order in the square brackets in the function)
Source: percentDifference and difference QuickSight Docs
Try -100 instead of -52. Since the 'wk' field is not a date-defined field, it is probably just considering 'wk' as an int.
I've a question about a rolling distinct count. I'm trying to calculate the latest 30 weeks (210 days) from a specific date (eg. Specific date = 18-02-2019 distinct count from 23-07-2018).
I've found a website/blog where this is explained, https://radacad.com/datesinperiod-vs-datesbetween-dax-time-intelligence-for-power-bi. But in some weird way, my calculation is not working.
My DAX expression:
Aantal mutaties afgelopen 30 weken:=
CALCULATE(
DISTINCTCOUNT(FCT_KlantReis_Mutatie[Mutatie]);
DATESINPERIOD(
FCT_KlantReis_Mutatie[Mutatiedatum];
LASTDATE(FCT_KlantReis_Mutatie[Mutatiedatum]) ;-210;DAY)
)
But in Excel (and PowerBI) I get the following result:
The table is linked to a date dimension. My guess is that it must be posible, but how...
Thanks in advance for the help.
I want to calculate sales for promotion using it's date. I need 3 measures, avg sales from 21 days before promotion start date, sales in between of promotion's start and end date, and sales from 21 days after promotion's end date.
Why Visual Studio highlights avg in code below?
CREATE MEMBER CURRENTCUBE.[Measures].[Sales in promotion]
AS Avg(Existing([Promotion].[Promotion name].[Promotion name]),[Measures].[Sales]), ...
Same in here:
CREATE MEMBER CURRENTCUBE.[Measures].[Sales before promotion]
AS (EXISTING([Promotion].[Promotion name].[Promotion name]), AVG(strtomember("[Date].[Date].&["+ [Promotion].[Date].currentmember.member_key+"]").lag(21) : strtomember("[Date].[Date].&["+ [Promotion].[Date From].currentmember.member_key+"]"),
[Measures].[Sales])) ...
If I do sum(existing()) in first measure, the sum is calculated correctly, but it doesn't allow me to get average.
EXISTING will only help if [Promotion] is part of your query in either the WHERE or SELECT clause. If it is not included in either of these clause then EXISTING will be finding 1 member - the All member.
You could try NonEmpty and maybe move the period logic into a custom set?
WITH
SET [PERIOD] AS
STRTOSET(
"[Date].[Date].&["+ [Promotion].[Date].currentmember.member_key+"].lag(21)
:
[Date].[Date].&["+ [Promotion].[Date From].currentmember.member_key+"]"
)
From the code you posted I cannot tell if you want a daily average or and average per promotion ? Say there were 2 promotions over the 21 days does this mean you want (Total/2/21) ?
I am trying to apply a measure value calculated at the Month level to a dimension contained within that month i.e.
Should look like this:
I've attempted to use a scoping statement so far but with no luck.
SCOPE (
{[Sale].[Sale Year].&[2]:[Sale].[Sale Year].&[7]}
,[Date].[Calendar Month].&[201603]
,[Measures].[Costs Per Sale] );
THIS = ([Date].[Calendar Month].&[201603],[Measures].[Costs Per Sale]);
END SCOPE;
The Aggregated Sales measure is calculated using the Sale Year which unfortunately has not and cannot be linked to the Cost dimension.
Does anyone know how I can apply the Cost Per Sale monthly value to the [Sale].[Sale Year] dimension?
Thanks
Try this -
SCOPE ({[Sale].[Sale Year].&[2]:[Sale].[Sale Year].&[7]} ,[Measures].[Costs Per Sale]);
THIS = ([Sale].[Sale Year].[All],[Measures].[Costs Per Sale]);
END SCOPE;
I have a table named "Historical_Stock_Prices" in a MS Access database. This table has the columns: Ticker, Date1, Open1, High, Low, Close1, Volume, Adj_Close. The rows consist of the data for each ticker for every business day.
I need to run a query from inside my VB.net program that will return a table in my program that displays the growth rates for each quarter of every year for each ticker symbol listed. So for this example I would need to find the growth rate for GOOG in the 4th quarter of 2012.
To calculate this manually I would need to take the Close Price on the last BUSINESS day of the 4th quarter (12/31/2012) divided by the Open Price of the first BUSINESS day of the 4th quarter (10/1/2012). Then I need to subtract by 1 and multiply by 100 in order to get a percentage.
The actual calculation would look like this: ((707.38/759.05)-1)*100 = -6.807%
The first and last days of each quarter may vary due to weekend days.
I cannot come up with the correct syntax for the SQL statement to create a table of Growth Rates from a table of raw Historical Prices. Can anyone help me with the SQL statment?
Here's how I would approach the problem:
I'd start by creating a saved query Access named [Stock_Price_with_qtr] that calculates the year and quarter for each row:
SELECT
Historical_Stock_Prices.*,
Year([Date1]) AS Yr,
Switch(Month([Date1])<4,1,Month([Date1])<7,2,Month([Date1])<10,3,True,4) AS Qtr
FROM Historical_Stock_Prices
Then I'd create another saved query in Access named [Qtr_Dates] that finds the first and last business days for each ticker and quarter:
SELECT
Stock_Price_with_qtr.Ticker,
Stock_Price_with_qtr.Yr,
Stock_Price_with_qtr.Qtr,
Min(Stock_Price_with_qtr.Date1) AS Qtr_Start,
Max(Stock_Price_with_qtr.Date1) AS Qtr_End
FROM Stock_Price_with_qtr
GROUP BY
Stock_Price_with_qtr.Ticker,
Stock_Price_with_qtr.Yr,
Stock_Price_with_qtr.Qtr
That would allow me to use the following query in VB.NET (or C#, or Access itself) to calculate the quarterly growth rates:
SELECT
Qtr_Dates.Ticker,
Qtr_Dates.Yr,
Qtr_Dates.Qtr,
(([Close_Prices]![Close1]/[Open_Prices]![Open1])-1)*100 AS Qtr_Growth
FROM
(
Historical_Stock_Prices AS Open_Prices
INNER JOIN Qtr_Dates
ON (Open_Prices.Ticker = Qtr_Dates.Ticker)
AND (Open_Prices.Date1 = Qtr_Dates.Qtr_Start)
)
INNER JOIN
Historical_Stock_Prices AS Close_Prices
ON (Qtr_Dates.Ticker = Close_Prices.Ticker)
AND (Qtr_Dates.Qtr_End = Close_Prices.Date1)