dax

I have two measures in my tabular cube. The first one called 'Number of Days' := CALCULATE(COUNTROWS(SUMMARIZE('A'[Date]))) The second one will includes the first one as its expression 'Number of Days (MTD)' := CALCULATE(TOTALMTD([Number of Days],'A'[Date])) The second measure when I browse the cube and pull out the measure. It runs incredibly slow. Any idea how I can optimize these measurements and make it run faster? Sample Data Volume:= SUMX(A, DIVIDE([Volume],2)) Volume (MTD):= TOTALMTD([Volume],'A'[Date]) Updated extra measurements The best practice should be creating a Calendar/Date

TL;DR: When using LOOKUPVALUE() against a table with Row Level Security, the RLS is not applied and all values are seen I have a requirement to have a 'default' value (location) picked in a Power BI report, based on the user. I am reporting against Azure Analysis Services (tabular model 1400) It appears that the way to implement default values in Power BI is to dynamically rename a value to something static, and pick that static value as a filter. So user Bob has default location Location1 so when he logs in he should be see his location user Joe has default location Location2 so he should be

I am looking to create a measure that takes the average of several sums, grouped by an ID. An example would be if you had a database of customers that each purchased a variety of things, and you wanted to find the average amount that customers spent total sum all of their purchases grouped by customer, and then average out the result. I have considered a group by table, but if I do this then filters will not apply correctly to the results (unless there is a way to create a relationship between the two in Power BI maybe, but I have not found that functionality). Is there a way to create this

Suppose I have a set of returns and I want to compute its beta values versus different market indices. Let's use the following set of data in a table named Returns for the sake of having a concrete example: Date Equity Duration Credit Manager ----------------------------------------------- 01/31/2017 2.907% 0.226% 1.240% 1.78% 02/28/2017 2.513% 0.493% 1.120% 3.88% 03/31/2017 1.346% -0.046% -0.250% 0.13% 04/30/2017 1.612% 0.695% 0.620% 1.04% 05/31/2017 2.209% 0.653% 0.480% 1.40% 06/30/2017 0.796% -0.162% 0.350% 0.63% 07/31/2017 2.733% 0.167% 0.830% 2.06% 08/31/2017 0.401% 1.083% -0.670% 0.29%

When I create a new measure with formula, i.e. sum(col1)/max(col2), it automatically converts the result into #.#% format. Strangely, it doesn't happen all the time; sometimes it just gives result #.## format. Any idea of how to format a new measure (not column) to be treated as percentage? In Power BI there is a option in the taskbar when you enter your measure. In Power Pivot for Excel you can select the format directly in the measure editor (Or editor for calculated fields. The name depends on your version of Excel) If you want to take over manually you can also use the Format() formula: =

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(

The goal is to create a visual that shows Budget vs Premium for each month in a year; Something like that: So I have two tables BudgetData and Premiums. How can I join those two table on two columns: `BudgetData.InsurenceType = Premiums.Division and BudgetData .MonthYear = Premiums.MonthYear` BudgetDate Table: InsurType Amount MonthYear Commercial Auto 1000 Jan 2017 Commercial Auto 22000 Feb 2017 Commercial Auto 3000 Mar 2017 Specialty Casualty 4000 Jan 2017 Specialty Casualty 5000 Feb 2017 Specialty Casualty 35000 Mar 2017 Premiums Table: Division Premium MonthYear Commercial Auto 2500 Jan

id datetime new_column datetime_rankx 1 12.01.2015 18:10:10 12.01.2015 18:10:10 1 2 03.12.2014 14:44:57 03.12.2014 14:44:57 1 2 21.11.2015 11:11:11 03.12.2014 14:44:57 2 3 01.01.2011 12:12:12 01.01.2011 12:12:12 1 3 02.02.2012 13:13:13 01.01.2011 12:12:12 2 3 03.03.2013 14:14:14 01.01.2011 12:12:12 3 I want to make new column, which will have minimum datetime value for each row in group by id. How could I do it in Power BI desktop using DAX query? Use this expression: NewColumn = CALCULATE( MIN( Table[datetime]), FILTER(Table,Table[id]=EARLIER(Table[id]) ) ) In Power BI using a table with your